Threat actors are actively exploiting CVE-2026-5027, a high-severity path traversal vulnerability in Langflow, a popular low-code platform for building AI applications. The flaw, disclosed in March, allows unauthenticated attackers to write files to arbitrary locations on vulnerable systems and potentially achieve remote code execution by abusing an unsanitized filename parameter in the platform’s file upload functionality.
The ‘POST /api/v2/files’ endpoint does not sanitize the ‘filename’ parameter from the multipart form data, allowing an attacker to write files to arbitrary locations on the filesystem using path traversal sequences (‘../’).
Researchers at VulnCheck observed attackers dropping test files on exposed systems, with roughly 7,000 internet-accessible Langflow instances potentially at risk. The vulnerability is particularly concerning because Langflow enables auto-login by default, allowing attackers to obtain a valid session token without credentials.
Andrew Obadiaru, CISO, Cobalt:
“From an attacker’s perspective, development platforms are often more attractive than the applications they produce because they can provide access to source code, credentials, deployment pipelines, and downstream systems. The fact that exploitation can begin with a single unauthenticated request significantly lowers the barrier to entry. Security teams should view AI development platforms as part of their critical attack surface and subject them to the same continuous testing and exposure management practices they apply to internet-facing business applications.”
Dale Hoak, CISO, RegScale:
“The rapid adoption of AI platforms and low-code AI development frameworks is creating a new class of operational risk that many organizations are still unprepared to manage at scale. Vulnerabilities like this highlight how quickly AI tooling can become part of the enterprise attack surface, often before governance, asset visibility, and security monitoring processes fully mature. When a flaw enables unauthenticated access and potential remote code execution, organizations need to immediately understand where these platforms are deployed, whether they are internet exposed, how quickly patches can be validated and applied, and what downstream systems may be impacted. As AI adoption accelerates, security teams need continuous visibility into AI-related assets, stronger configuration governance, and automated assurance processes capable of identifying and responding to emerging risks in near real time.”
This is another call to action when it comes to low code tools that are used in business. They can be used as good or bad in business. Don’t be on the bad side.
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This entry was posted on June 11, 2026 at 12:14 pm and is filed under Commentary with tags Langflow. You can follow any responses to this entry through the RSS 2.0 feed.
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Threat Actors exploiting High Severity Vulnerability in Langflow
Threat actors are actively exploiting CVE-2026-5027, a high-severity path traversal vulnerability in Langflow, a popular low-code platform for building AI applications. The flaw, disclosed in March, allows unauthenticated attackers to write files to arbitrary locations on vulnerable systems and potentially achieve remote code execution by abusing an unsanitized filename parameter in the platform’s file upload functionality.
The ‘POST /api/v2/files’ endpoint does not sanitize the ‘filename’ parameter from the multipart form data, allowing an attacker to write files to arbitrary locations on the filesystem using path traversal sequences (‘../’).
Researchers at VulnCheck observed attackers dropping test files on exposed systems, with roughly 7,000 internet-accessible Langflow instances potentially at risk. The vulnerability is particularly concerning because Langflow enables auto-login by default, allowing attackers to obtain a valid session token without credentials.
Andrew Obadiaru, CISO, Cobalt:
“From an attacker’s perspective, development platforms are often more attractive than the applications they produce because they can provide access to source code, credentials, deployment pipelines, and downstream systems. The fact that exploitation can begin with a single unauthenticated request significantly lowers the barrier to entry. Security teams should view AI development platforms as part of their critical attack surface and subject them to the same continuous testing and exposure management practices they apply to internet-facing business applications.”
Dale Hoak, CISO, RegScale:
“The rapid adoption of AI platforms and low-code AI development frameworks is creating a new class of operational risk that many organizations are still unprepared to manage at scale. Vulnerabilities like this highlight how quickly AI tooling can become part of the enterprise attack surface, often before governance, asset visibility, and security monitoring processes fully mature. When a flaw enables unauthenticated access and potential remote code execution, organizations need to immediately understand where these platforms are deployed, whether they are internet exposed, how quickly patches can be validated and applied, and what downstream systems may be impacted. As AI adoption accelerates, security teams need continuous visibility into AI-related assets, stronger configuration governance, and automated assurance processes capable of identifying and responding to emerging risks in near real time.”
This is another call to action when it comes to low code tools that are used in business. They can be used as good or bad in business. Don’t be on the bad side.
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This entry was posted on June 11, 2026 at 12:14 pm and is filed under Commentary with tags Langflow. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.