High-Severity Flaws in Langflow and vLLM Expose Secrets and Enable RCE
Two high-severity vulnerabilities were disclosed in widely used AI application components, affecting Langflow and vLLM. In Langflow, CVE-2026-33497 impacts versions before 1.7.1 and stems from improper filtering of folder_name and file_name in the /profile_pictures/{folder_name}/{file_name} endpoint. The path traversal flaw (CWE-22) allows unauthenticated attackers to read files across directories, including the application's secret_key, creating a direct risk of secret exposure and follow-on compromise. The issue is addressed in Langflow 1.7.1 and tracked in GitHub advisory GHSA-ph9w-r52h-28p7.
A separate flaw in vLLM, CVE-2026-27893, can lead to remote code execution by bypassing a user's attempt to disable remote code trust. In versions from 0.10.1 up to but not including 0.18.0, two model implementation files hardcoded trust_remote_code=True, overriding the safer --trust-remote-code=False setting and allowing malicious model repositories to run code during model use. The vulnerability, classified as CWE-693, was patched in vLLM 0.18.0, underscoring supply-chain and configuration-bypass risks in AI infrastructure components.

Get ahead of threats like this
Mallory correlates global threat intelligence with your attack surface — know if you’re exposed before adversaries strike.
How this story unfolded
4 events from the most recent confirmed update back to the earliest known activity.
vLLM 0.18.0 patches CVE-2026-27893
vLLM version 0.18.0 fixed the hardcoded trust_remote_code=True behavior in NemotronVL and KimiK25 model implementations. GitHub security advisories on the CVE referenced the fixing commit, pull request, and advisory.
vLLM discloses CVE-2026-27893 trust_remote_code bypass
A vulnerability in vLLM versions 0.10.1 through before 0.18.0 was disclosed after researchers found two model implementation files hardcoded trust_remote_code=True, overriding users' explicit security opt-out. This could enable remote code execution from malicious model repositories.
Langflow 1.7.1 patches CVE-2026-33497
Langflow version 1.7.1 was identified as containing the fix for CVE-2026-33497, addressing the file-reading issue in the profile picture download handler. The advisory references GitHub Security Advisory GHSA-ph9w-r52h-28p7.
Langflow discloses CVE-2026-33497 path traversal flaw
A path traversal vulnerability affecting Langflow versions before 1.7.1 was disclosed, involving insufficient filtering of folder_name and file_name in the /profile_pictures/{folder_name}/{file_name} endpoint. The flaw could allow attackers to read files across directories, including the application's secret_key.
Related entities
Vulnerabilities, threat actors, malware, products, organizations, and breaches Mallory has linked to this story.
Sources
2 references tracked. Mallory keeps watching after this page renders.
CVE-2026-27893 - vLLM's hardcoded trust_remote_code=True in NemotronVL and KimiK25 bypasses user security opt-out
cvefeed.io
Open sourceCVE-2026-33497 - Langflow: /profile_pictures/{folder_name}/{file_name} endpoint file reading
cvefeed.io
Open sourceSee the full picture, correlated to your attack surface.
Map indicators from this story to your assets and identify affected systems in minutes.
Every observed campaign, victim, and pivot linked to actors named in this story.
Malware, exploits, and IOCs connected to the activity described here.
YARA, Sigma, and Snort rules deployed to your SIEM as soon as they’re published.
Get matching new stories delivered to your team as they break — not the next morning.
Ask questions about this story and take action on the answers.


