Category: Press Releases

Tel Aviv, Israel, September 30th, 2026, CyberNewswire

Legit Security today announced an expansion of its Agentic Remediation capability to cover vulnerabilities found in open-source dependencies, not just first-party code – enabling development teams to move from vulnerability detection to a verified fix without manual triage.

The expansion addresses a growing gap in application security: as AI-generated code accelerates software delivery, most modern codebases are made up largely of open-source dependencies, and every new package introduces potential exposure to known vulnerabilities. Traditional find-it, fix-it AppSec workflows, which rely on human teams working down a backlog, can’t keep pace with that volume – particularly when the vulnerable code isn’t in a company’s own codebase but several layers deep in a third-party package.

Legit’s Agentic Remediation previously focused on fixing static analysis findings in code written by a company’s own engineers. With this release, the same agent now takes on vulnerabilities introduced through dependencies, extending verified remediation to the other major source of vulnerabilities in modern software.

“The real challenge isn’t finding vulnerabilities anymore – it’s getting from finding to fix fast enough,” the company said, noting that AI-generated code has multiplied the volume of software shipping daily while attackers increasingly use AI to find and exploit those vulnerabilities faster than defenders can respond.

How it works

When pointed at a vulnerable dependency, the agent:

• Identifies the dependency – the vulnerable package, its current version, and whether it’s a direct or indirect (transitive) dependency.
• Finds the safest upgrade – the smallest version bump that resolves the issue, staying within the current major version where possible to avoid breaking changes.
• Applies the fix – updates the dependency configuration and regenerates the lockfile, including any other instances of the vulnerable version elsewhere in the dependency tree.
• Verifies the fix – re-scans the dependency before and after the change to confirm the vulnerability is resolved and no new issue was introduced.
• Opens a pull request – delivering a ready-to-review PR with the fix and vulnerability details attached.

Every fix is re-scanned before a PR is opened, so developers receive a change that has already been verified rather than a suggested version to try.

Handling major version upgrades

When a fix requires crossing a major version boundary – where breaking API changes become a risk – the agent adds an AI-assisted analysis layer that evaluates how the specific repository uses the package and proposes the source code adaptations needed, validated against the real repository and package data.

Legit draws a clear distinction in these cases: the dependency fix itself is verified through re-scanning, like any other remediation, while the code adaptation for a major version jump is AI-assessed rather than independently verified. The company said the PR flags this distinction explicitly, so developers know what’s been verified and what warrants closer review before merging.

About Legit Security

Legit positions the expansion as part of a broader effort to close the gap between detection and a safe, verified fix across both first-party code and open-source dependencies – the two primary sources of vulnerabilities in modern software – without relying on manual backlog triage.

Contact

Dave Howell
Legit Security
dave@legitsecurity.com

San Francisco, USA, September 29th, 2026, CyberNewswire

Archipelo today announced Salmon, Execution Verification Infrastructure (EVI) for AI agents and autonomous systems, powered by a cryptographic protocol designed to make execution history verifiable. Salmon establishes verifiable execution history and state lineage across humans, AI agents, and automation.

The launch follows the OpenAI–Hugging Face incident, in which OpenAI reported that models participating in cybersecurity evaluations circumvented isolation controls, gained internet access, exploited vulnerabilities, accessed third-party systems, collaborated and delegated work across agents, and took actions their developers did not direct. OpenAI called the incident a “warning shot” and said sophisticated AI systems require safeguards that operate at the speed of the agents themselves.

AI agents use credentials, invoke tools, execute code, call APIs, delegate work to other agents, modify infrastructure and change production state. As these systems operate across multiple actors and systems, the resulting state does not by itself preserve the execution history that produced it.

Salmon is designed to capture execution as signed events and record the state transitions they produce, providing machine-consumable execution evidence for investigation, detection and response, remediation, supervision and accountability across AI security, safety, control and governance systems.

Archipelo is backed by Dell Technologies Capital and technology investors including Zoom CEO Eric Yuan, Andy Bechtolsheim, Bill Tai, David Weisburd, Hack VC, Sangha Capital and Nima Capital. Its team brings experience spanning NASA, DoD, AWS, Google, Cisco, Meta, Harvard, MIT and Berkeley.

Execution Verification for AI Security and Control

Identity establishes who or what is acting. Authorization determines what an actor may do. Runtime controls determine whether execution should proceed. Observability monitors behavior.

Execution Verification addresses a different question: What executed, and can that history be independently verified?

Salmon is designed to provide an execution evidence layer for autonomous systems.

From Execution to a Verifiable Execution Record

Salmon captures execution as signed events and records the state transitions they produce. Each event identifies the actor, action, state before, state after and cryptographic signature. Salmon links these events into a Verifiable Execution Record, preserving the lineage between execution and resulting state.

Capture → Execution Record → State Lineage → Verification

The record produces Machine-Consumable Execution Evidence that downstream systems can verify and use automatically.

Salmon establishes the execution record. Other systems reason from it.

When execution evidence is unavailable, Salmon preserves the gap rather than manufacturing continuity.

Execution Evidence for AI Security and Safety

“You cannot control autonomous systems without verifiable evidence of their execution,” said Matthew Wise, Creator & Protocol Architect of Salmon and CEO of Archipelo. “AI safety is becoming an execution problem. As agents gain the authority to use credentials, invoke tools, delegate actions and change production systems — safety and control cannot depend only on what a model was instructed to do, permitted to do, or says it did. We need verifiable evidence of what executed and what changed. Salmon provides that missing evidence.”“Powerful AI should not be responsible for establishing the history of its own execution. Capture the evidence when execution happens. Make it cryptographically verifiable. Let AI safety, control, security and governance systems reason from the record.”

Salmon is intended to provide structured execution evidence for machine-speed supervision, investigation, detection and response, remediation and accountability across autonomous systems.

Autonomous Systems and Execution Evidence

Verifiable execution history provides AI safety, control, security and governance systems with evidence they can use as autonomous systems execute and modify software and infrastructure.

“Agentic AI is creating a powerful tradeoff: agent autonomy and productivity also mean software systems increasingly act without direct human oversight,” said Bill Tai, investor in Archipelo. “As AI agents gain greater authority across production systems — the ability to verify what executed and what changed becomes foundational. Salmon provides the execution evidence needed to strengthen agent safety, control, and governance.”

From DevSPM to Salmon

Salmon grew out of Archipelo’s R&D work on Developer Security Posture Management and software actor attribution. As AI evolved from assisting developers to executing actions across tools, credentials and infrastructure, Archipelo expanded its work from software actor attribution to execution history and state lineage.

DevSPM made software actors observable. Salmon makes their execution history verifiable.

About Salmon

Salmon provides verifiable execution history for autonomous multi-actor software systems.

Salmon is Execution Verification Infrastructure for autonomous systems — powered by a cryptographic protocol — establishing verifiable execution history and state lineage across humans, AI agents and automation.

Salmon is developed by Archipelo, Inc.

Users can learn more: salmon.systems

Contact

Stan Kapusta
Archipelo, Inc
stan@archipelo.co

Austin, Texas / USA, September 9th, 2026, CyberNewswire

Ninety-five percent of organizations believe they have visibility into their AI and machine identity exposures, yet only 36% are actually monitoring them.

SpyCloud, the leader in identity threat protection, today released its annual SpyCloud Identity Threat Report, a survey-based study finding that non-human identities (NHIs) – the AI agents, service accounts, API keys, and authentication tokens that connect to internal systems – have become the most common route attackers take into the enterprise.

SpyCloud 2026 Identity Threat Report, Source: SpyCloud

The survey found that compromised NHIs (31%) are nearly 2x as likely to be the primary entry point compared to phishing and social engineering (17%), the second-ranked answer. NHI-related misuse was also the most commonly reported identity-based event type at 42%, yet the vast majority of organizations aren’t watching for them. While 95% of organizations believe they have adequate visibility into AI- and NHI-related exposures, only 36% monitor them, making machine identities the least-watched category of identity risk in the report. Further amplifying the problem, 68% of organizations experienced an identity-based event in the same period, with those affected averaging eight events each.

Organizations typically maintain a clear inventory of their human workforce, but few extend that same visibility to the service accounts, API keys, and AI agents authenticating into their systems every day. These identities are provisioned for convenience and often hold real privilege, yet in most environments nobody owns them: a service account doesn’t get off-boarded, doesn’t rotate its own credentials, and doesn’t fail an MFA challenge, so once one is exposed it can stay usable for months.

“That asymmetry is what attackers are exploiting,” said Trevor Hilligoss, SpyCloud’s Chief Intelligence Officer. “Every one of these identities is a standing invitation that renews itself until someone notices.”

This year’s report is based on a survey of 750 cybersecurity leaders and practitioners at organizations with 500+ employees across North America (US and Canada), the United Kingdom, and select European markets – Spain, Germany, the Netherlands, Austria, and Switzerland. It benchmarks how organizations detect, remediate, and govern identity threats across human and non-human identities.

Additional key findings include:

• AI adoption has outpaced governance. Nearly all organizations (91%) use AI tools or agents with access to internal systems, applications, or data, but only 56% have formal governance and ownership for the resulting privileges. Another 41% rely on informal processes or partial ownership, leaving shadow access – privileged connections operating outside normal governance and monitoring.
• Exposed session blind spots track with higher event rates. Organizations that had visibility into stolen session cookies experienced identity-based events at a meaningfully lower rate (37%) than those that could not (50%).
• Session cookies and tokens let attackers bypass authentication controls like MFA by resuming an already-authenticated session. This gives them trusted access to applications and data, it’s no surprise then that SpyCloud research shows that session data has overtaken passwords as attackers’ top target.
• Phishing and malware remain the delivery mechanism. Phishing and social engineering is cited as a common access path for identity events (37%) with 40% reporting incomplete visibility into successful phishing attacks, and 53% can see malware exposures on managed devices only.
• Malware and exposed access top the list of supply chain identity events. Malware-infected third-party devices (23%) and exposed API keys or application access involving vendors and partners (22%) were the leading reported causes of supply chain identity events.
• Third-party exposures are getting found, but not closed. Nearly 40% of organizations have no consistent process to confirm that a third-party identity exposure was actually resolved, even as 32% name enhancing supply chain and vendor risk management among their planned investments for the next 12 to 18 months.

Non-human identities and third-party exposures are creating new paths into the enterprise, while stolen sessions give attackers ways around controls designed to protect authenticated users.

“Every control that works pushes attackers toward what it doesn’t cover – we hardened passwords, so they targeted sessions; we tightened employee accounts, so they looked to service accounts and vendor connections,” added Hilligoss. “SpyCloud continues to track threat actor behavior closely to understand where attackers are moving, what data they value, and how those patterns evolve over time.”

Continuous monitoring & automation separate the most resilient identity programs

Identity exposure creates an ongoing operational burden that extends well beyond the initial incident, and how quickly organizations respond has a direct impact on business outcomes. Those relying on manual, case-by-case remediation reported higher incident response costs than organizations with high levels of automation (39% versus 32%) and greater loss of customer or partner trust (47% versus 36%).

The report also introduces SpyCloud’s Identity Threat Protection Maturity Model, which groups respondents into four maturity tiers – Reactive, Building, Operational, and Optimized – across identity exposure visibility, monitoring, governance, automation, and remediation. The findings reflect that the more mature an identity program gets, the more it relies on continuous identity exposure monitoring and automated remediation – and that combination is what actually drives incident rates down.

At enterprise scale, some share of an organization’s employees, vendors, and machine accounts will be exposed in the near future regardless of how strong its controls are. What changes business outcomes is how long that exposure stays usable.

“Most identity programs are still measured on whether an exposure happened. That’s the wrong scoreboard,” said Damon Fleury, Chief Product Officer at SpyCloud. “Organizations that pair continuous identity monitoring with automated remediation of workforce exposures create the greatest friction for criminals and gain the biggest edge in preventing follow-on attacks.”

Users can access the full, no form-fill 2026 SpyCloud Identity Threat Report and benchmark their organization against the Identity Threat Protection Maturity Model by taking the free assessment here.

About SpyCloud

SpyCloud transforms recaptured darknet data to disrupt cybercrime. Its automated identity threat protection solutions use advanced analytics and AI to accelerate investigations and protect workforce, consumer, and supplier identities from the threats that matter most: authentication bypass, session hijacking, malicious insiders, account takeover, ransomware, and fraud. Its data from malware-infected devices, successful phishes, combolists, and third-party breaches also powers many popular dark web monitoring and identity theft protection offerings. Customers include 7 of the Fortune 10, along with hundreds of global enterprises, mid-sized companies, and government agencies worldwide. Headquartered in Austin, TX, SpyCloud is home to more than 250 cybersecurity experts whose mission is to protect businesses and consumers from the stolen identity data criminals are using to target them now.

To learn more and see insights on your company’s exposed data, visit spycloud.com.

Contact

Account Director
Emily Brown
REQ on behalf of SpyCloud
spycloud@req.co

Boston, MA, USA, September 8th, 2026, CyberNewswire

Specialized team of AI agents that discover, attack, and validate web vulnerabilities, leveraging pre-existing site context to eliminate noise and speed remediation.

Reflectiz, the continuous web exposure management company, today launched a multi-agent penetration testing platform for websites. Multiple specialized AI agents discover, attack, and validate vulnerabilities across complex web environments, and because they start from an existing model of each site, they cover up to ten times more than conventional pentesting tools.

A pentest used to be an event. An engagement, a report, done. The report described a moment. The website kept going: login, checkout, payments, dozens of third-party scripts, all probed by attackers daily.

“Websites change every week and get pentested once or twice a year. That gap is where exposure builds up,” said Idan Cohen, CEO and co-founder of Reflectiz. “Teams need testing that keeps up with releases at a cost they can sustain, and trusted coverage of what was tested.”

While others start every test blind, Reflectiz already knows the website.

Reflectiz has spent a decade scanning thousands of production websites and holds a live model of each one: pages, scripts, third parties, domains, sensitive inputs, and behaviors. The pentesting agents add the attacker’s perspective to that same model.

A finding does not arrive as a line item. It arrives with the script involved, the data it can reach, and whether real users are exposed right now, allowing teams to skip the investigation and go straight to the fix.

“The hard part of web pentesting was never the payload. It was understanding what the application actually does,” said Ysrael Gurt, CTO and co-founder of Reflectiz. “Our engine has been reading live websites for years, so our agents start with a map of the site that other tools never build.”

A team of specialized agents, not another scanner

The agentic pentesting runs as a coordinated team of AI agents, each with a defined role:

• One agent crawls the site the way a real user does, through logins, one-time codes, and 2FA, mapping what is actually there.
• A second fingerprints the stack and works out which attacks apply where.
• A third runs those attacks and chains what it finds.
• The fourth matters most: an independent validator reproduces every finding before it reaches the report. False positives are removed by design.

The result: findings with reproduction steps and evidence, plus a coverage map of what was tested and cleared.

Testing spans the full OWASP Top 10, and teams set depth per flow, from fast predefined checks to expert-level attack chains on critical assets.

Completing the 360° map of web risk

The agentic pentesting, part of the new Offensive Hub, joins Security Hub and Privacy Hub on the Reflectiz platform, completing a 360° map of web risk: what runs on the website, what data it touches, and how it can be attacked.

• One exposure picture. Findings from all three hubs cross-reference automatically, no dashboards reconciled by hand.
• Guided fixes. Atlas, the Reflectiz AI remediation agent, explains each risk and walks the team through the fix.
• Existing workflows. Results route into current operations through a REST API, CI/CD triggers, and Slack alerts.

See it live

Reflectiz founders Idan Cohen and Ysrael Gurt will demonstrate the agentic pentesting in a live webinar on September 15 at 11 AM ET / 6 PM CET.

Registration: https://www.reflectiz.com/lp/founders-case-study-webinar/

Product information: Reflectiz Offensive Hub | Walkthrough Video

About Reflectiz

Reflectiz is the continuous web exposure management company. Its agentless, outside-in platform monitors, tests, and secures the entire web layer, from third-party scripts and web privacy risk to agentic penetration testing of the live site. Reflectiz helps enterprises in retail, finance, travel, insurance, healthcare, and gaming meet PCI DSS, DORA, NIS2, and global privacy requirements without touching a line of code. Learn more at https://www.reflectiz.com.

Contact

Marketing Manager
Oran Frenkel
Reflectiz
oran.f@reflectiz.com

New York, NY, United States, September 8th, 2026, CyberNewswire

Mars Security, the autonomous threat hunting and detection engineering platform founded by offensive security veterans, today announced Real-Time Intel-Based Detection, a capability that turns newly published threat intelligence into validated, ready-to-deploy detection rules within minutes of release.

Built by former offensive operators, the new capability converts advisories from CISA, Mandiant, and other intelligence sources into MITRE ATT&CK-mapped detection rules across CrowdStrike, Wiz, Splunk, and cloud telemetry, each one tested against 30 days of the customer’s own data before it goes live.

Mars believes it is the first platform to automate the complete path from threat advisory to production detection, including backtesting against the customer’s own environment, with no data ingestion and no changes to the existing security stack.

Every security team already pays for threat intelligence. Very little of it becomes a working detection. When CISA, Mandiant, Unit 42 or Microsoft Threat Intelligence publishes a report on a new campaign, malware family or APT group, a detection engineer still has to read it, pull the indicators and techniques, work out which log source can see them, write the query, test it, tune it and deploy it. Across most SOCs that cycle takes days to weeks. Attackers rotate infrastructure in hours. That delay, the gap between knowing about a threat and being able to detect it, is where most successful intrusions sit.

Mars now closes that gap automatically.

How it works

As new intelligence becomes available, Mars extracts the relevant indicators, techniques and infrastructure, maps them to MITRE ATT&CK, and writes the detection in the native query language of whichever telemetry can actually see the threat: CrowdStrike Falcon, Wiz, Splunk, firewall logs, Linux Sysmon, identity providers, AWS telemetry, or data lakes such as Snowflake and Databricks. Each rule carries a severity rating and lands in the team’s queue for review. Accept Rule pushes it live. Dismiss clears it.

Nothing ships untested. Before a rule is offered, Mars runs the exact query against the customer’s previous 30 days of data and shows how many events it would have matched and how many of those would have been false positives. Teams can rerun the backtest over any window they choose. The same scrutiny applies to the underlying indicators: domains, IP addresses and hashes are scored against their false-positive history, and anything too broad, too old or historically noisy is dropped before it ever reaches a rule.

“We spent years on the offensive side, and the thing that surprised us most was how rarely anyone saw us, even when the intel on our tradecraft was already public. Threat intelligence has always told security teams what is happening in the world. It never handed them the detection to find it in their own environment. Mars does that now, and it tests the detection against your data before it goes anywhere near production.” – Shahaf Galili, Co-Founder and CEO, Mars Security.

Coverage, not just alerts

The engine also works in the other direction. Mars continuously maps the customer’s existing detection coverage against the telemetry already connected and flags the gaps that matter. Recent recommendations include AWS CloudTrail logging tampering, Route 53 domain transfer abuse, pass-the-hash lateral movement and suspicious Microsoft Graph API activity. For teams running detection-as-code, select recommendations arrive as an open pull request, ready to review and merge.

That matters because static rules break the moment attacker tradecraft shifts. Mars was built by people who spent years watching detections fail from the other side, and its hunt library targets behavior rather than signatures so coverage holds as adversaries change tools. The same engine now extends to newer attack surfaces, including monitoring AI coding agents and the credentials they leak into logs, without buying another tool to watch them.

“A SOC should not need a two-week backlog to act on a report that took an attacker two hours to make obsolete. When the intel lands, the detection should already be written, already tested against your data, and waiting for a click.” – Ran Lerer, Co-Founder and CTO, Mars Security.

“A campaign advisory used to sit in a queue for days before it became a rule anyone trusted. With Mars, it shows up already mapped, already tested against the environment it’s meant to protect, and it actually holds up. That is the first time detection has felt ahead of the threat instead of behind it.” – Andy Ellis, Former CISO, Akamai Technologies.

Availability

Real-Time Intel-Based Detection is available now to all Mars Security customers at no additional cost. Mars deploys in hours, requires no data ingestion, no tool replacement and no additional detection engineering headcount, and is available on AWS Marketplace.

Security teams can request a demo or read the technical documentation on the Mars website.

About Mars Security

Mars Security is the autonomous threat hunting and detection engineering platform that continuously converts threat intelligence into validated detections across an organization’s existing security stack. Founded by offensive security veterans Shahaf Galili, Ran Lerer and Matan Caspi, who bring more than 50 years of combined hands-on cyber offense experience, Mars queries SIEM, EDR, identity, cloud and data lake telemetry in place, with no ingestion and no rip-and-replace, and turns advisories into MITRE ATT&CK-mapped, backtested detection rules in minutes. Mars maps detection coverage gaps, delivers a behavior-based threat hunting library built from years of offensive operations, and replaces the patch treadmill with continuous detection engineering. Mars is SOC 2 compliant, available on AWS Marketplace, and backed by TLV Ventures, Jibe Ventures, Bullet Ventures, CCL and XPS.

Learn more at marssec.ai, download the Mars one-pager, read the Mars blog or follow Mars Security on LinkedIn.

Contact

Nir Lerer
Mars Security
Nir@Marssec.ai

Bnei Brak, Israel, August 31st, 2026, CyberNewswire

New capability identifies, attributes and validates API keys, OAuth tokens and other machine credentials stolen from developer and employee endpoints

Lunar Cyber today announced Token Exposure Monitoring, a new capability designed to identify, attribute and validate Non-Human Identities (NHI) and machine credentials inside infostealer logs, connect them to the affected organization, and determine which exposures require action.

The rapid adoption of AI development tools, cloud platforms and automated infrastructure has put a new class of credentials on developer machines: API keys, OAuth tokens, personal access tokens, and other machine identities that provide direct access to valuable services.

Security researchers have documented the theft and abuse of AI API credentials for attacks such as LLMjacking, where stolen keys are used to run expensive AI workloads through a victim’s account. Developer credentials can also provide access to source-code repositories, cloud infrastructure, SaaS platforms and corporate data. Lunar’s internal research found that modern infostealers actively collect the local files and application data where these credentials are frequently stored.

Developers routinely authenticate to services such as AWS, GitHub, OpenAI, Anthropic, Slack, Okta and other cloud and development platforms from their workstations. Tokens can be stored in .env files, application configuration, CLI authentication files, shell history, browser data and local caches. Modern infostealers use file-grabber components to collect exactly this type of endpoint data.

The growing use of AI development tools has expanded that exposure. Persistent API and OAuth credentials are increasingly used by AI APIs, command-line agents and developer environments, placing valuable machine credentials directly on endpoints targeted by malware.

“Developer tokens have become valuable credentials in their own right,” said Ran Geva, Founder and CEO of Webz.io. “A stolen AI key can be converted into compute almost immediately. A GitHub token can provide access to source code, and a cloud credential can open infrastructure. Security teams need visibility into these credentials at the moment they appear in an infostealer log, with enough context to understand who they belong to and what needs to be revoked.”

From an Anonymous Token to an Actionable Incident

Machine credentials create a different intelligence problem from traditional compromised passwords. An exposed corporate email address carries its organizational identity inside the credential. An API token generally appears as an opaque string with little indication of who owns it.

Lunar analyzes the surrounding infostealer data to solve that attribution problem. The platform associates exposed secrets with the compromised employee or organizational endpoint, identifies the service and credential type, and retains forensic evidence showing where the secret appeared.

For supported credentials, Lunar also checks their validation state. Analysts can distinguish between findings based on service, credential type, severity and validation status rather than treating every token-like string as an equivalent alert.

The Token Exposure interface provides access to the exposed credential, affected employee, service, internal file path, original log context, malware metadata and other information collected from the compromised endpoint. Analysts can search and filter exposures by service, employee, token type, breach date, severity and validation state.

Extending infostealer response beyond passwords and sessions

Most infostealer response processes center on cleaning the infected endpoint, resetting passwords and invalidating browser sessions. Machine credentials introduce another remediation path because API keys, PATs, OAuth tokens and other secrets frequently follow independent authentication lifecycles and can remain usable until they are rotated or revoked.

Lunar Token Exposure Monitoring adds machine credential discovery to that response process. Once an affected token is identified, security teams can rotate or revoke the credential and investigate activity within the corresponding service.

The capability complements repository secret scanning, secrets management and NHI security products. Those systems help organizations control machine identities internally, while Lunar provides intelligence about credentials that have already been extracted from an endpoint by malware.

“Passwords and cookies have been at the center of infostealer response for years,” Geva said. “Developer tokens now deserve the same treatment. If the malware took the credential, the incident response process needs to find it, validate it and rotate it.”

Token Exposure Monitoring is available in Lunar Essential & PRO Tiers.

About Lunar Cyber

Lunar Cyber provides compromised-credential intelligence that helps organizations identify and investigate employee exposure originating from data breaches and infostealer malware. Lunar combines Webz.io’s collection infrastructure with forensic context, validation and response workflows to help security teams identify compromised access and respond quickly.

For more information, users can visit lunarcyber.com.

Contact

CEO
Ran Geva
Webz.io LTD
ran@webz.io

Adelaide, Australia, August 19th, 2026, CyberNewswire

Independent assessment provides Australian organisations with additional evidence when evaluating application control for sensitive, government, defence and critical infrastructure environments.

Airlock Digital, a global provider of application control and allowlisting solutions, today announced that it has completed an independent Information Security Registered Assessors Program (IRAP) assessment at the PROTECTED classification level.

The assessment was conducted by an Australian Signals Directorate (ASD)-endorsed IRAP assessor against the Australian Government Information Security Manual (ISM). It provides Australian organisations with additional independent evidence when evaluating Airlock Digital’s security controls and their alignment with applicable Australian Government security expectations, including the ISM and Protective Security Policy Framework (PSPF).

For Australian security teams, confidence in a technology provider depends on more than features. It also means understanding how that provider approaches security, how its controls stand up to independent scrutiny, and whether it can support the security requirements of sensitive environments.

The completion of the assessment gives organisations additional information for their due diligence, including those considering cloud-based application control as part of a broader security architecture.

Why This Matters to Australian Organisations

IRAP provides access to independent security assessments designed to help organisations understand the security strengths and weaknesses of information and communications technology systems and services.

Airlock Digital’s completion of an IRAP assessment at the PROTECTED level provides further independent assurance for Australian organisations assessing whether the company’s technology fits their security, governance, cloud and risk requirements.

Across the Australian market, organisations are placing increasing emphasis on independent security assurance. Organisations working with government, defence and critical infrastructure frequently need to demonstrate that the technologies on which they depend have been assessed against recognised Australian Government security expectations.

For organisations adopting cloud services, this assurance can form part of a broader assessment of how security controls, deployment architecture, governance and operational responsibilities fit within their own risk models.

For organisations working toward stronger security maturity or alignment with the Essential Eight Maturity Model, the question is increasingly not simply whether potentially malicious activity can be detected, but whether teams can clearly define what should be allowed to run in the first place.

Application control is already an important part of the Australian cyber security conversation, and Airlock Digital has a history of supporting Australian organisations with demanding security requirements.

Supporting Different Infrastructure Strategies

Australian organisations increasingly operate across a mix of cloud, on-premises, hybrid and highly constrained environments. Application control must work within those operating models rather than force organisations into a single architecture.

Airlock Digital offers flexible deployment approaches, including cloud-delivered and on-premises models, enabling organisations to align application control with their infrastructure strategies and security requirements.

For environments with particularly strict connectivity requirements, application control can also be implemented without depending on continuous external cloud connectivity. This is particularly relevant to organisations operating sensitive, segmented, air-gapped or otherwise constrained environments.

What the Assessment Means for Organisations Evaluating Airlock Digital

In addition to Airlock Digital’s existing security and privacy reports and certificates, the IRAP assessment provides independent evidence to support customer due diligence.

This includes organisations evaluating different deployment approaches. Airlock Digital supports application control across environments in which organisations may need to balance cloud adoption with specific security, operational, connectivity or infrastructure requirements.

Airlock Digital helps organisations define what runs across their endpoint environments. Rather than relying solely on generic definitions of trusted software, organisations retain ownership of their trust decisions and use Airlock Digital to operationalise allowlisting as an ongoing process.

With Airlock Digital, security and IT teams can:

• Prevent unauthorised software from executing.
• Establish and retain ownership of clear, organisation-defined trust decisions.
• Maintain visibility into what runs across endpoint environments.
• Support application control across cloud-connected, on-premises and constrained environments.
• Work toward a Deny by Default posture while maintaining operational stability.

These principles are central to the Airlock Digital approach: clear ownership of trust, predictable enforcement, and security controls that work across real-world environments.

For Airlock Digital and its customers, the value of the IRAP assessment is straightforward: independent scrutiny, useful evidence for customer due diligence, and another way to help Australian security teams make informed and defensible technology decisions.

Organisations considering Airlock Digital can contact the company to discuss the assessment and its scope, available deployment options, and how Airlock Digital can help them define what runs while maintaining operational stability.

Learn more by visiting the Airlock Digital IRAP page or check out the blog announcement.

About Airlock Digital

Airlock Digital helps organizations stop threats before they start through preventative endpoint security. Founded in Australia in 2013 and operating internationally, the company provides precision application control, allowlisting and OS hardening that enable organizations to run only trusted software and reduce attack surfaces. Airlock Digital supports customers across financial services, healthcare, manufacturing, energy, government and education. Learn more at airlockdigital.com.

Contact

VP of Marketing
Erin Welke
Airlock Digital
erin.welke@airlockdigital.com