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Hackers are targeting sensitive information stored in the LiteLLM open-source large-language model (LLM) gateway by exploiting a critical vulnerability tracked as CVE-2026-42208.
The flaw is an SQL injection issue that occurs during LiteLLM’s proxy API key verification step. An attacker can exploit it without authentication by sending a specially crafted Authorization header to any LLM API route.
This allows reading data from the proxy’s database and modifying it. According to the maintainer’s security advisorythreat actors could use it for “unauthorised access to the proxy and the credentials it manages.”
A fix was delivered in LiteLLM version 1.83.7 to replace string concatenation with parameterized queries.
LiteLLM stores API keys, virtual and master keys, and environment/config secrets, so accessing its database allows hackers to read sensitive data they may then use to launch additional attacks.
LiteLLM is a popular proxy/SDK middleware layer that enables users to call AI models via a single unified API. The project is widely used by developers of LLM apps and platforms managing multiple models. It has 45k stars and 7.6k forks on GitHub.
The project has also recently been targeted in a supply-chain attack, where TeamPCP hackers released malicious PyPI packages that deployed an infostealer to harvest credentials, tokens, and secrets from infected systems.
In a report from researchers at Sysdig, a cloud security company, say that CVE-2026-42208 exploitation started approximately 36 hours after the bug was disclosed publicly on April 24.
Active exploitation activity
The researchers observed deliberate and targeted exploitation attempts that sent crafted requests to ‘/chat/completions’ with a malicious ‘Authorization: Bearer’ header.
These requests queried specific tables that contained API keys, provider (OpenAI, Anthropic, Bedrock) credentials, environment data, and configs.
Sysdig explained that there were no probes against benign tables, and “the operator went straight to where the secrets live,” a strong indicator that the attacker knew exactly what to target.
In the second phase of the attack, the threat actor switched IP addresses, likely for evasion, reran the same SQL injection attempts, but focused on the correct table names and structures derived in the previous phase, now using fewer, more precise payloads.
Sysdig comments that, while 36 hours is not as quick as exploiting a recent flaw in Marimo, the attacks were targeted and specific.
The researchers warned that exposed LiteLMM instances still running vulnerable versions should be treated as potentially compromised, and every virtual API key, master key, and provider credential stored in internet-exposed LiteLLM instances should be rotated.
For those who can’t upgrade to LiteLLM 1.83.7 and later, the maintainers suggest the workaround of setting ‘disable_error_logs: true’ under ‘general_settings’ to block the path through which malicious inputs can reach the vulnerable query.
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Hackers are actively exploiting a critical vulnerability in LiteLLM, an open-source gateway for large language models (LLMs). The flaw, tracked as CVE-2026-42208, is an SQL injection issue that occurs during the proxy’s API key verification process. Attackers can exploit it without authentication by sending a maliciously crafted Authorization header to any LLM API route, allowing them to read or even modify data in the proxy’s database.
According to the project’s security advisory, this vulnerability could grant unauthorized access to the proxy and the sensitive credentials it manages. A patch was released in LiteLLM version 1.83.7, replacing unsafe string concatenation with secure parameterized queries. Since LiteLLM stores API keys, master keys, and environment secrets, a successful breach could expose highly sensitive data, which attackers might leverage for further attacks.
LiteLLM is a widely used middleware layer that simplifies interactions with multiple AI models through a unified API. Popular among LLM developers, the project boasts over 45,000 GitHub stars and 7,600 forks. Unfortunately, it has recently faced multiple security threats, including a supply-chain attack where malicious PyPI packages distributed an infostealer to harvest credentials from compromised systems.
Exploitation of CVE-2026-42208 began roughly 36 hours after its public disclosure on April 24. Attackers sent carefully crafted requests to the /chat/completions endpoint, using manipulated Authorization: Bearer headers to query tables containing API keys, provider credentials (such as OpenAI and Anthropic), and configuration data. Notably, the attackers bypassed benign tables entirely, zeroing in on the most sensitive data—suggesting they knew exactly what to target.
In a second phase, the attackers switched IP addresses, likely to evade detection, and refined their SQL injection attempts with more precise payloads. While the exploitation wasn’t as rapid as some recent attacks, it was highly targeted and methodical.
Security experts warn that any exposed LiteLLM instances running vulnerable versions should be considered compromised. Organizations are urged to rotate all stored API keys, master keys, and provider credentials immediately. For those unable to upgrade to LiteLLM 1.83.7 or later, a temporary workaround involves disabling error logs by setting disable_error_logs: true in the general_settings configuration.
As AI security risks escalate, threat actors are chaining vulnerabilities to bypass defenses, signaling a growing wave of sophisticated exploits. Proactive measures, including timely patching and credential rotation, are essential to mitigate these threats.
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