01 Information We Collect
SigmaSec collects only what it needs to scan, prioritise and help remediate vulnerabilities:
- Account information (name, work email address, organization identity, authentication credentials).
- Vulnerability finding metadata (CVE IDs, EPSS scores, CVSS vectors, file paths and tool execution logs).
- Short code snippets around a vulnerable dependency's call sites, used for the dependency usage check.
- For committed secrets, a masked value and a hash only; raw secret values are never stored.
- Audit records of actions such as scans started, settings changed and fix pull requests opened.
- On the hosted service, repository contents are cloned temporarily during a scan and deleted afterwards.
02AI Inference & Model Data Usage
SigmaSec uses an AI model to explain findings in plain English and suggest remediation. You choose the model: a local Ollama model, or Anthropic's Claude API.
- Local option: with Ollama, prompts never leave your deployment.
- Claude option: prompts are sent to Anthropic's API and handled under Anthropic's commercial terms.
- Before any prompt is sent, recognisable secrets (API keys, tokens, private keys, JWTs) are redacted.
- SigmaSec does not use customer code, findings or prompts to train or fine-tune models.
03Data Storage & Security Controls
Current controls (self-hosted deployments inherit the controls of the infrastructure you run them on):
- Encryption in transit: traffic to the SigmaSec web app and API is served over HTTPS.
- Integration credentials: GitHub, Jira and Slack tokens are encrypted at the application layer before storage.
- Tenant isolation: every query is scoped to your organisation in the application layer.
- Audit logging: scans, settings changes and integration actions are recorded in an audit log.
04 Contact Information
For questions regarding this policy or data protection inquiries, contact our data protection team directly at privacy@sigmasec.ai.