Prompt injection instructions
- Finding
- Prompt-injection style instruction pattern detected.
Security checks across static analysis, malware telemetry, and agentic risk
This is a coherent AI sales-agent template, but it merits Review because it can autonomously contact customers, persist and reinject customer data, and includes guidance to hide that the agent is AI.
Install only if you are comfortable operating an autonomous sales agent. Before production use, disclose AI involvement to recipients, require human approval for outbound campaigns and quotes, limit API/channel credentials, inspect deploy scripts, and configure retention, deletion, and sanitization for customer memory.
VirusTotal findings are pending for this skill version.
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
Customers or leads may believe they are interacting with a human representative, creating consent, compliance, and reputation risks for the business using the skill.
The skill's customer-facing behavior explicitly instructs the AI not to reveal that it is AI and to present as a sales consultant, which can mislead external recipients.
Nunca revela identidad de IA — se presenta como tu consultor de ventas
Change the persona rules to disclose AI assistance clearly and ensure all outreach complies with platform rules and local marketing laws.
If configured broadly, the agent could send messages, follow-ups, quotes, or sales commitments to real leads without enough operator review.
The skill is designed to perform end-to-end external sales activity across messaging and email channels; the top-level instructions do not clearly require per-message or per-deal human approval.
handles lead capture → qualification → follow-up → quoting → closing across WhatsApp, Telegram, and email
Require human approval for first outreach, quotes, discounts, deal-closing language, and bulk campaigns; configure allowlists, rate limits, and audit logs.
Customer PII, budgets, objections, quotes, and commitments may be retained and reused across sessions; malicious or accidental instructions captured in memory could steer later conversations.
The design stores customer conversation data every turn and later injects memory into the system prompt, which can expose sensitive customer/business data and allow untrusted customer text to influence future behavior if not sanitized.
ChromaDB Per-Turn Storage — Every turn stored with customer_id isolation ... Add the following dynamic section to the Agent's System Prompt
Treat retrieved memory as untrusted data, escape or label customer-provided text, add retention/deletion controls, and avoid injecting raw customer content into system-level instructions.
The agent may keep processing conversations, updating memory, and triggering workflows in the background after initial setup.
The documented hooks and cron behavior are disclosed and purpose-aligned, but they create continuing background activity beyond a single user-invoked task.
auto-execute after each turn ... run as a Cron skill checking for new completed conversations every minute
Make cron jobs opt-in, document how to stop them, and monitor background actions with logs and alerts.
Misconfigured or overprivileged keys could let the agent access messaging accounts, model accounts, or deployment infrastructure more broadly than intended.
The skill expects operational credentials for servers, AI providers, and communication channels. This is expected for an SDR integration, but the registry metadata declares no required credentials.
Edit config.sh with your server, API keys, and channel settings
Use least-privilege API keys, separate test and production credentials, rotate secrets, and avoid storing real credentials in repository files.
Running deployment scripts may modify a server and install or upload code that affects agent behavior.
The deployment flow can install dependencies and change the skill set on a target server. This is relevant to the stated deployment purpose, but it expands the trust boundary.
deploy.sh now auto-uploads all local skills from `skills/` directory ... auto-installs Python3 + graphify on target server
Review deployment scripts and dependency sources before running them, pin versions where possible, and use a staging environment first.