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Skill scan report

telegram-crabbox-e2e-proof

View on GitHub
24 Low Automated analysis flagged 2 potential risk patterns.

What this skill does

The skill is designed for use in PR review or bug reproduction workflows involving Telegram, specifically for testing and proving behavior with a real Telegram user session on Crabbox. It involves lea

github/openclaw - credential_leasing - 385.8k stars

Threatscredential_leasing data_exfiltration_risk

Threat analysis

credential_leasing1 finding
data_exfiltration_risk1 finding

Skill info

Nameopenclaw/telegram-crabbox-e2e-proof
Registrygithub
Versionc39abce
PURLpkg:github/openclaw/openclaw@c39abce?skill=telegram-crabbox-e2e-proof
Stars385.8k

Assessments (2)

credential_leasing1 finding HIGH
HIGH

credential_leasing via local-llm-review

SKILL.md

leases the exclusive `telegram-user` Convex credential
data_exfiltration_risk1 finding MEDIUM
MEDIUM

data_exfiltration_risk via local-llm-review

SKILL.md

starts a 24fps desktop recording

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How Anomity governs this at runtime

Scan-time vetting tells you what a skill says it will do. Anomity's Endpoint Sensor sees what agents actually do: it discovers skills alongside every other AI artifact on the endpoint, and runtime governance can allow, deny, or log the tool calls a skill triggers. Policy violations route to your SIEM, Slack, email, or Jira, backed by a queryable 90-day audit trail.

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Methodology and disputes

Every skill is assessed by the Anomity Skill Intelligence engine against its public source; findings indicate risk patterns, not confirmed exploitation. Maintainer of telegram-crabbox-e2e-proof? Report an issue or request a rescan.

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