Attackers Exploit Critical Langflow and Rails Flaws in Credential-Probing and C2 Activity

Threat actors are exploiting two critical flaws impacting Langflow and Ruby on Rails, according to new findings from VulnCheck.

The vulnerabilities in question are listed below –

• CVE-2026-0768 (CVSS score: 9.8) – A lack of proper validation of a user-supplied input vulnerability that could be exploited to execute arbitrary Python code in the context of the root user.
• CVE-2026-66066 aka KindaRails2Shell (CVSS score: 9.5) – A vulnerability that could allow an unauthenticated attacker to read arbitrary files from the server, leak Rails process environment and secrets such as secret_key_base, the Rails master key, database passwords, cloud storage credentials, and API tokens, ultimately leading to remote code execution.

Attackers can exploit CVE-2026-66066 by uploading a crafted image by taking advantage of the discrepancy between Active Storage and libvips in how they read input files. Successful exploitation requires affected applications to use libvips for Active Storage image processing and accept image uploads from untrusted users.

VulnCheck said it recorded more than 50 detections within a few hours on August 30, 2026, a figure that has since risen to 360 as of Monday.

“Adversaries appear to be conducting a mix of reconnaissance and credential harvesting activities: Among other things, attacker requests are querying environment variables (LANGFLOW_SUPERUSER, OPENAI_API*, AWS_ACCESS*, AWS_SECRET*), reading /root/.cache/langflow/secret_key, and checking .ssh access and .bash_history size,” Caitlin Condon, vice president of threat research at VulnCheck, said.

“Source traffic primarily originates from Russia and has thus far exclusively hit Canaries in the U.K.”

The exploitation comes as threat actors have exploited as many as 12 vulnerabilities since 2025, with more than 15,000 successful attempts leveraging CVE-2026-0769, CVE-2025-3248, and CVE-2026-5027. The majority of the vulnerable Langflow hosts are located in the U.S., Germany, Malaysia, Brazil, and India.

In one case observed against its canary systems, unknown threat actors have been observed exploiting CVE-2026-5027 to drop a Python credential harvester, proxy agents, and SimpleHelp for remote access. In another, attackers have weaponized CVE-2025-3248 to enlist the machine into an XMR cryptocurrency miner botnet.

“They then disabled auditd, resulting in a forensic blind spot, and exploited CVE-2026-0769 to drop .sysd,” VulnCheck said. “From there, the attacker pivoted to scan for other targets, likely to expand their cryptomining operation, and moved on to another host.”

The findings highlight increased threat actor interest in AI development platforms, which can provide access to sensitive credentials, cloud environments, and other connected systems.