Credentials from AI Agent Configuration - AI Security Technique
AI Security TechniqueAdversaries may access the credentials of other tools or services on a system from the configuration of an AI agent. AI Agents often utilize external tools or services to take actions, such as querying databases, invoking APIs, or interacting with cloud resources. To enable these functions, credentials like API keys, tokens, and connection strings are frequently stored in configuration files. While there are secur...
Overview
A source-backed snapshot of this AI security technique.
Adversaries may access the credentials of other tools or services on a system from the configuration of an AI agent.
AI Agents often utilize external tools or services to take actions, such as querying databases, invoking APIs, or interacting with cloud resources. To enable these functions, credentials like API keys, tokens, and connection strings are frequently stored in configuration files. While there are secure methods such as dedicated secret managers or encrypted vaults that can be deployed to store and manage these credentials, in practice they are often placed in less protected locations for convenience or ease of deployment. If an attacker can read or extract these configurations, they may obtain valid credentials that allow direct access to sensitive systems outside the agent itself.
Technique details
Identifiers, maturity, and source taxonomy for this technique.
- ATLAS ID
- AML.T0083
- Maturity
- demonstrated
- Priority score
- 40
Attack flow
How to read the public records connected to this technique.
Impact
Why this technique may deserve attention in the current dataset.
- Evidence leveldemonstrated
- Mapped defenses0 ATLAS mitigation records
- Public examples2 linked case study records
- Research risks0 related MIT AI Risk records above the confidence threshold
- Vulnerabilities0 linked CVE records
Mitigations
Defenses that may help against this attack.
Case studies
Examples from public reports and exercises.
Exposed ClawdBot Control Interfaces Leads to Credential Access and Execution
A security researcher identified hundreds of exposed ClawdBot control interfaces on the public internet. ClawdBot (now OpenClaw) “is a personal AI assistant you run on your own devices. It answers you on the channels you already use … , plus extension channels. … It can speak and listen on macOS/iOS/Android, and can render a live Canvas you control.”[1] The researcher was able to access credentials to a variety of connected applications via ClawdBot’s configuration file. They were also able to invoke ClawdBot’s skills by prompting it via the chat interface, leading to root access in the container.
The researcher searched Shodan[2] to identify Clawdbot instances exposed on the public internet, some without authentication enabled. The researcher demonstrated that the ClawdBot’s authentication mechanism could be bypassed due to a proxy misconfiguration.
With access to ClawdBot’s control interface, they were then able to access ClawdBot’s configuration, which contained credentials to a variety of other services. Across various exposed instances of ClawdBot, they identified Anthropic API Keys, Telegram Bot Tokens, Slack Oauth Credentials, and Signal Device Linking URIs. The researcher prompted ClawdBot directly via the chat interface, which led to exposure of its system prompt. They were also able to get ClawdBot to execute commands via it’s bash skill, which at least in once instance led to root access in the ClawdBot container.
The researcher noted a broad range of other impacts they could have had with this level of access, including:
- Manipulation of user chat history with the ClawdBot AI agent
- Exfiltration of conversation histories of any connected messaging services
- Impersonation of users by sending messages on their behalf via connected messaging services
References
Data Exfiltration via an MCP Server used by Cursor
The Backslash Security Research Team demonstrated that a Model Context Protocol (MCP) tool can be used as a vector for an indirect prompt injection attack on Cursor, potentially leading to the execution of malicious shell commands.
The Backslash Security Research Team created a proof-of-concept MCP server capable of scraping webpages. When a user asks Cursor to use the tool to scrape a site containing a malicious prompt, the prompt is injected into Cursor’s context. The prompt instructs Cursor to execute a shell command to exfiltrate the victim’s AI agent configuration files containing credentials. Cursor does prompt the user before executing the malicious command, potentially mitigating the attack.
Source evidence
Original public records and references for this page.
Original source
Original source links
Open the public records and source datasets used for this page.