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Home/CyberSecurity News/Critical LiteLLM SQL Injection Vulnerability Actively
CyberSecurity News

Critical LiteLLM SQL Injection Vulnerability Actively

A critical pre-authentication SQL injection vulnerability affecting LiteLLM, an open-source AI gateway, is now actively being exploited in the wild. LiteLLM is widely used and boasts over 22,000...

Jennifer sherman
Jennifer sherman
April 28, 2026 2 Min Read
0 0

A critical pre-authentication SQL injection vulnerability affecting LiteLLM, an open-source AI gateway, is now actively being exploited in the wild. LiteLLM is widely used and boasts over 22,000 GitHub stars.

Tracked as CVE-2026-42208, this severe flaw allows unauthorized attackers to extract highly sensitive cloud and AI provider credentials directly from the platform’s PostgreSQL database.

LiteLLM acts as a central proxy for major language models like OpenAI, Anthropic, and AWS Bedrock.

Because it manages AI routing and billing, the application stores high-value secrets, including master API keys and enterprise cloud credentials.

Rapid Exploitation and Targeted Data Theft

The blast radius of a successful breach is closer to that of a massive cloud account compromise than to that of a typical web application attack.

The vulnerability exists within the proxy’s verification process. Specifically, LiteLLM fails to protect the Authorization Bearer header securely.

By inserting a single quote into a fake token like sk-litellm’, an attacker can break out of the intended query and run malicious database commands before authentication even takes place.

Any HTTP client that can reach the proxy port can execute the exploit.

The Sysdig Threat Research Team detected the first exploitation attempt just 36 hours and seven minutes after the vulnerability was indexed in the global GitHub Advisory Database on April 24, 2026.

Rather than using noisy, automated vulnerability scanners, the attackers demonstrated advanced knowledge of LiteLLM’s internal structure.

The threat actors launched targeted attacks against three tables: LiteLLM_VerificationToken, litellm_credentials, and litellm_config.

These tables store the system’s most critical data, including virtual API keys, stored provider credentials, and environment configurations.

The operators even adapted their payloads to match the exact case of the database schema.

This highly targeted activity originated from two IP addresses (65.111.27.132 and 65.111.25.67) within the same autonomous system, indicating a coordinated, deliberate data-extraction effort.

Immediate Patching and Credential Rotation

The maintainers of LiteLLM have released version 1.83.7, which resolves the vulnerability by properly securing the database queries.

Organizations running any affected version (from 1.81.16 through 1.83.6) must apply this critical update immediately.

Because this attack requires no login and can be executed against any exposed instance, administrators should assume that vulnerable, internet-facing servers have already been compromised.

Security teams must instantly rotate all virtual API keys, master keys, and stored provider credentials.

Furthermore, companies should actively monitor their upstream cloud billing accounts for unexpected API calls or unauthorized AI token consumption.

Defenders should also audit web server logs for suspicious requests containing SQL keywords or the sk-litellm’ payload.

As AI gateways become major repositories for expensive cloud credentials, they must be treated as top-tier security targets.

Securing these proxy environments behind internal networks and maintaining strict patch management are essential steps to prevent devastating corporate credential theft.

Disclaimer: HackersRadar reports on cybersecurity threats and incidents for informational and awareness purposes only. We do not engage in hacking activities, data exfiltration, or the hosting or distribution of stolen or leaked information. All content is based on publicly available sources.

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Jennifer sherman

Jennifer sherman

Jennifer is a cybersecurity news reporter covering data breaches, ransomware campaigns, and dark web markets. With a background in incident response, Jennifer provides unique insights into how organizations respond to cyber attacks and the evolving tactics of threat actors. Her reporting has covered major breaches affecting millions of users and has helped organizations understand emerging threats. Jennifer combines technical knowledge with investigative journalism to deliver in-depth coverage of cybersecurity incidents.

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