Systematic hunt for hardcoded credentials, API keys, certificates, and default passwords in extracted IoT firmware. Covers /etc/shadow and passwd parsing, busybox httpd configs, telnet/dropbear stanzas, MQTT/cloud API key extraction, and cross-referencing against known default-credential databases.
63
75%
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Critical
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tessl review fix ./packages/decepticon/decepticon/skills/standard/iot/hardcoded-creds/SKILL.mdSecurity
2 findings: 1 critical severity, 1 high severity. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
This playbook explicitly instructs how to discover, extract, and crack embedded credentials and private keys from firmware (including host keys, authorized_keys, cloud tokens, JWTs), and discusses using those artifacts for SSH access and MitM—enabling credential theft, unauthorized access, and large-scale compromise.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The playbook explicitly runs commands that extract and print plaintext/hashed passwords, API tokens, JWTs, and private keys and saves cracked plaintexts to evidence files, which requires the agent/LLM to handle and potentially output secret values verbatim.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
This required workflow operates on extracted rootfs files from a provided/targeted firmware image (`/tmp/squashfs_root`), and it ingests that outsider-authored content into the LLM context indirectly via evidence strings/captured findings (e.g., printing/searching/cracked outputs such as `/tmp/all_strings.txt`, `/tmp/unshadowed.txt`, and evidence files), which would be treated as text derived from the outsider firmware rather than operating-user-authored data.
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