devopsy.kinsta.cloud

Tag: ASPM

  • Cycode Acquires Bearer to Extend ASPM Platform

    Cycode Acquires Bearer to Extend ASPM Platform

    Cycode today announced it had acquired Bearer, a provider of a set of tools for static application security testing (SAST), discovering application programming interfaces (APIs) and identifying sensitive data.

    The provider of an application security posture management platform (ASPM) plans to integrate the Bearer tools into its core platform to enable DevSecOps teams to further consolidate tooling.

    Cycode CEO Lior Levy said the acquisition of Bearer gives Cycode access to a set of tools that take advantage of generative artificial intelligence (AI) to surface suggestions that enable DevSecOps teams to more easily secure modern applications based on, for example, a microservices-based architecture.

    Bearer achieves that goal by continuously scanning for application security issues as developers are writing code, he added. Overall, Bearer claims its approach to scanning is 31% faster than rival tools while simultaneously leveraging tools such as Bearer Assist, currently in beta, to provide more context concerning the level of risk to the business any issue discovered actually represents.

    Those capabilities will be infused into the Risk Intelligence Graph (RIG) that Cycode developed for its ASPM platform.

    Cycode earlier this year added generative AI capabilities to its platform to make it simpler for DevSecOps teams to identify the root cause of vulnerabilities in complex distributed computing environments. The company uses the generative AI platform created by OpenAI to provide a natural language interface for RIG. As part of that effort, Cycode is making available an executive dashboard that, based on all the dependencies uncovered, provides summaries of risks that make it easier to discern what is occurring across an application environment.

    The company is at the forefront of developing ASPM platforms that continuously ingest data to identify and assess application security risks. Those platforms also provide a foundation for consolidating many of the tools that DevSecOps teams currently rely on to secure applications before they are deployed in production environments.

    It’s not clear how quickly organizations are embracing DevSecOps best practices, but given the number of vulnerabilities that continue to be discovered, there is still much work to be done. The challenge is that legacy tools that lack AI capabilities were not designed to enable organizations to practically shift more responsibility left toward application development teams that typically don’t have a lot of cybersecurity expertise, noted Levy. AI makes it possible to now provide those teams with the context required to address application security issues as they write code versus just before applications are deployed, he added.

    In theory at least, the applications deployed today should be significantly more secure than previous generations of applications. In effect, IT environments are steadily becoming more secure. Less apparent, however, is the rate at which modern applications are being deployed to replace legacy applications that are, all too often, rife with known vulnerabilities that cybercriminals can easily exploit. Given the rate at which vulnerabilities can be discovered and patched in those legacy applications, it may take the better part of the rest of this decade to address those issues once and for all.

  • Cycode Brings Generative AI to App Security Posture Management

    Cycode Brings Generative AI to App Security Posture Management

    Cycode today added generative artificial intelligence (AI) capabilities to its application security posture management (ASPM) platform to make it simpler for DevSecOps teams to identify the root cause of vulnerabilities in complex distributed computing environments.

    At the same time, Cycode is adding plugins for VS Code and JetBrains integrated development environments, a command line interface and pull request scanners to make it easier to identify security issues as early as possible during the software development life cycle (SDLC). Cycode also revealed today it now has more than 75 connectors to various security tools commonly used within DevSecOps workflows.

    Amir Kazemi, director of product marketing for Cycode, said the company is using OpenAI’s generative AI platform to provide a natural language interface for invoking the Risk Intelligence Graph that is at the core of the Cycode ASPM platform. As part of that effort, Cycode is now also making available an Executive Dashboard that, based on all the dependencies uncovered, provides summaries of risks that make it easier to discern what is occurring across an application environment.

    The platform, as a result, can now provide automated risk scoring for vulnerabilities based on actual severity and potential impact to the business, said Kazemi. The overall goal is to make it simpler to secure software supply chains by facilitating the proactive collaboration between application developers, DevOps engineers and cybersecurity professionals, he added.

    It’s not clear what impact generative AI is going to have on how DevSecOps workflows are constructed, but making it easier to identify the root cause of security issues in application environments made up of monolithic applications, microservices and event-driven frameworks is now essential. Application security has simply become too chaotic to effectively manage without help from AI, noted Kazemi. In its current state, application security is simply unmanageable, he added.

    The challenge is that just because a zero-day vulnerability has been discovered, it doesn’t always follow that application development teams know where every instance of it exists within their application environment. It’s not uncommon for DevSecOps teams to discover outdated versions of components that have known vulnerabilities to be running months after a patch in an updated version of that component has been made available.

    DevSecOps teams are, of course, always trying to strike a balance between the level of threat a vulnerability represents and the possibility that the patch that should be applied might break an application. However, given the risk to application environments, it’s becoming less risky to patch an application than it is to hope that cybercriminals don’t exploit a known vulnerability.

    While much DevSecOps progress has been made in recent years, it’s clear there is still much work to be done. Hopefully, generative AI will make it simpler for application development teams to address issues more rapidly than ever. In the meantime, however, DevSecOps teams should assume cybercriminals are looking to exploit the same AI capabilities to discover vulnerabilities they can exploit faster than ever.

  • Legit Security Adds Sensors to Detect Usage of Gen AI Tools to Write Code

    Legit Security Adds Sensors to Detect Usage of Gen AI Tools to Write Code

    Legit Security today announced it has added the ability to detect when developers use generative artificial intelligence (AI) tools to write code to its application security posture management (ASPM) platform.

    The ASPM platform developed by Legit Security already has discovery capabilities for application secrets, for example, enabled by sensors that are now being extended to include generative AI tools.

    Legit Security CTO Liav Caspi said the overall goal is to allow DevSecOps teams to identify who uses these tools to write which types of code. Each DevSecOps team can then decide how stringently to enforce policies to either ban or limit usage of those tools, he added.

    There is no doubt that generative AI tools are increasing developer productivity, but the large language models (LLMs) that provide the ability to generate code were trained using examples of code of varying quality collected from across the web. Much of that code either contains known vulnerabilities or is simply inefficient, which can manifest itself in the output surfaced by a generative AI platform.

    The Legit Security ASPM platform, in addition to identifying generative AI tools being used in real-time, can also be employed to scan the LLM itself to identify security risks such as prompt injection and insecure output handling. Unfortunately, most cybersecurity teams are unaware of the extent to which application code generated by a machine might be insecure, so it currently falls to leaders of DevSecOps teams to determine what is an acceptable use of these tools. It may be perfectly fine to rely on a generative AI tool to create a script that will be used for an internal-facing application. However, using the same tool to write business logic that will be exposed to the internet may not be especially prudent.

    It’s not clear how much of the code finding its way into software builds is being generated by a machine versus a human. In the longer term, the goal is to be able to identify that code by, for example, detecting substantial changes in the way code is normally written by a human developer, said Caspi.

    Of course, while an ASPM may detect usage of generative AI tools that are connected to a corporate environment, there are still plenty of opportunities for developers to use these tools offline to create code that can later be added to a build using a code check-in tool. After all, many developers have used various shadow IT tools to write code for decades. Regardless of who or what wrote that code, however, it should still be reviewed.

    In the meantime, the overall size of the codebase that DevSecOps teams will need to manage and secure will only exponentially increase as developers become more productive. Hopefully, more AI capabilities will soon be embedded into DevOps platforms to further automate the management of software builds at a time when many DevOps teams were already finding themselves overwhelmed even prior to the rise of generative AI.

  • Bionic Extends Application Security Posture Management Platform

    Bionic Extends Application Security Posture Management Platform

    Bionic this week added a pair of tools to its application security posture management (ASPM) platform that make it simpler to triage threats based on severity and attach a risk score.

    Josh Cho, senior director of global systems engineering at Bionic, said the Bionic Signals and Business Risk Scoring tools ingest data from third-party security tools to provide analytics capabilities. The first two vendors with which Bionic has integrated its ASPM platform are Wiz and Sonatype.

    The goal is to partner with additional vendors that provide unique cybersecurity capabilities that don’t compete with one another, said Cho.

    The agentless Bionic ASPM platform enables organizations to manage application risks by continuously collecting data from services and their dependencies, application programming interfaces (APIs) and DevOps data flows both in pre-production environments and after applications are deployed. Bionic then assesses any changes made to those environments based on a set of cybersecurity policies it provides. If an issue is discovered, the platform will create an alert informing the appropriate development team of best practices that eliminate the issue.

    While there is a lot of effort being made to shift more responsibility left toward application developers, there is often not enough cybersecurity context provided, said Cho. Bionic’s ASPM platform aggregates data from multiple tools to enable DevSecOps teams to better prioritize their remediation efforts, he added.

    It’s not clear how much organizations have embraced DevSecOps best practices, but one of the issues that needs to be addressed is the often-conflicting alerts generated by the various tools being used. Bionic is making a case for an ASPM platform that synthesizes data from multiple sources to streamline DevSecOps workflows.

    One way or another, more organizations will be embracing DevSecOps to better secure their software supply chains as more regulations are mandated. The challenge they face today is that most application developers—and the DevOps teams that support them—don’t have a lot of cybersecurity expertise. As a result, it becomes difficult to discern which vulnerabilities require immediate attention and which can be addressed in a regular update. In some instances, an alert generated by a cybersecurity team may not even been relevant—because the application in question is not internet-facing or the impacted module has not been loaded.

    In fact, it’s that very lack of context that often results in application developers disregarding the alerts generated by cybersecurity teams. Whenever there is a breach, however, cybersecurity teams always demand to know why their alert was ignored.

    No developer, of course, deliberately sets out to build and deploy vulnerable applications. In the race to meet delivery deadlines, there are always going to be tradeoffs. The issue then becomes keeping track of the cybersecurity technical debt that accumulates over time. An ASPM solution provides a means to keep track of that debt to enable DevSecOps teams to keep the risk in perspective.

  • Snyk to Add ASPM Platform via Enso Security Acquisition

    Snyk to Add ASPM Platform via Enso Security Acquisition

    Snyk this week announced it plans to acquire Enso Security, a provider of an application security posture management (ASPM) solution that tracks events and analyzes metadata collected from DevOps and security tools.

    At the same time, Snyk revealed it has added a DeepCode AI Fix tool that creates validated fixes for code written by either humans or machines and an Insights tool that helps organizations better prioritize remediation efforts based on the risk to the business. DeepCode AI Fix extends the capabilities of a generative artificial intelligence (AI) capability based on large language models (LLMs) that Snyk gained with the acquisition of DeepCode in 2020.

    Manoj Nair, chief product officer for Snyk, said all of these initiatives represent an effort to extend the reach of Snyk’s portfolio to address a wider range of issues within the context of a larger DevSecOps workflow as well as give developers tools that enable them to write more secure code.

    The acquisition of Enso Security is expected to close this quarter. The company has been making a case for an ASPM platform that eliminates the need to manually collect cybersecurity data from the various tools and platforms that a DevOps team may be using.

    Despite innumerable cybersecurity concerns, the rate at which applications are being deployed and updated continues to accelerate. The Enso platform makes it possible for cybersecurity teams to keep pace with those projects by discovering issues before an application is deployed in a production environment.

    The challenge, of course, is that most development teams are not going to be able to address every issue before an application needs to be deployed. In addition to knowing who is developing what application code, cybersecurity teams need to also prioritize potential issues versus rather than just sharing a list of potential issues that have been discovered. Enso Security’s ASPM platform provides visibility into events so that it’s simpler for cybersecurity teams to trace issues back to individual developers or the AI platform that generated them.

    That latter issue is becoming more significant as more development teams rely on general-purpose generative AI platforms to write code, noted Nair. Those platforms are writing that code based on samples collected across the internet, many of which are deeply flawed from a cybersecurity perspective, he added.

    The Enso platform is intended to enable cybersecurity teams to have the most impact on an application development project without being forced to interrogate every developer to determine what’s occurring in any application environment. In fact, one of the reasons developers resent those conversations is they know all the relevant data has already been entered into a system—cybersecurity professionals just need to access it.

    There’s still a lot of work to be done when it comes to bridging the historic divide between cybersecurity professionals and application developers. However, the more data that can be seamlessly shared between these teams, the simpler it becomes for organizations to embrace DevSecOps best practices.