Record summary
A quick snapshot of what this page covers.
Attack context
How this AI attack works in practice.
Adversaries may attempt to use their access to an AI agent on the victim's system to retrieve data from available agent tools to collect credentials. Agent tools may connect to a wide range of sources that may contain credentials including document stores (e.g. SharePoint, OneDrive or Google Drive), code repositories (e.g. GitHub or GitLab), or enterprise productivity tools (e.g. as email providers or Slack), and local notetaking tools (e.g. Obsidian or Apple Notes).
- ATLAS ID
- AML.T0098
- Priority score
- 43
Mitigations
Defenses that may help against this attack.
AML.M0032 - Segmentation of AI Agent Components
Segmentation can prevent adversaries from utilizing tools in an agentic workflow to harvest credentials.
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.”[<sup>\[1\]</sup>][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[<sup>\[2\]</sup>][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 Remote Poisoned MCP Tool
Researchers at Invariant Labs demonstrated that AI agents configured with remote Model Context Protocol (MCP) Tools can be vulnerable to model poisoning attacks. They show that an MCP Tool can contain malicious prompts in its docstring description, which is ingested into the AI agent’s context, modifying its behavior.
They demonstrate this attack with a proof-of-concept MCP Tool that instructs the agent to perform additional actions before using the tool. The agent is instructed to read files containing credentials from the victim’s machine and store their contents in one of the input variables to the tool. When the tool runs, the victim’s credentials are exfiltrated to the poisoned MCP server.
Source
Where this page information comes from.
Original source
Original source links
Open the public records and source datasets used for this page.