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Soc2 Evidence Collector

作者 afrexai-cto · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install afrexai-soc2-evidence-collector
功能描述
Generate SOC2 evidence collection checklists, automate evidence gathering scripts, and produce audit-ready evidence packages. Covers all 5 Trust Service Crit...
使用说明 (SKILL.md)

SOC2 Evidence Collector

Automate evidence gathering for SOC2 Type I and Type II audits across all 5 Trust Service Criteria.

When to Use

  • Preparing for an upcoming SOC2 audit (Type I or Type II)
  • Building continuous compliance evidence pipelines
  • Auditor requests evidence and you need to gather it fast
  • Onboarding a new client who requires SOC2 compliance proof
  • Annual evidence refresh cycle
  • Gap analysis before engaging an audit firm

Input

Gather these from the user before generating:

Required

  1. Audit type: Type I (point-in-time) or Type II (over a period, typically 3-12 months)
  2. Trust Service Criteria in scope: Security (CC — always required), plus any of: Availability, Processing Integrity, Confidentiality, Privacy
  3. Cloud provider(s): AWS, GCP, Azure, multi-cloud, on-prem, hybrid
  4. Primary tech stack: languages, frameworks, CI/CD, IaC tools
  5. Team size: engineering + ops headcount

Optional

  • Current compliance certifications (ISO 27001, HIPAA, PCI-DSS, etc.)
  • Audit firm name and timeline
  • Previous audit findings or gaps
  • Specific control frameworks already mapped (NIST 800-53, CIS, etc.)
  • SSO/IdP provider (Okta, Azure AD, Google Workspace, etc.)

Evidence Categories

CC — Common Criteria (Security) — Always In Scope

CC1: Control Environment

Evidence Source Collection Method
Org chart with security roles HR system / Confluence Manual export quarterly
Security policy documents Policy repo / wiki Git log showing annual review
Code of conduct acknowledgments HR system Export signed acknowledgments
Board/management meeting minutes on security Calendar + notes Screenshot + agenda export
Risk assessment documentation GRC tool / spreadsheet Export current risk register

CC2: Communication and Information

Evidence Source Collection Method
Security awareness training records LMS / training platform Completion report export
Onboarding security checklist HR system Template + completion logs
Incident communication procedures Runbook / wiki Version-controlled doc with review history
External communication policies Policy repo Git log + approval records

CC3: Risk Assessment

Evidence Source Collection Method
Annual risk assessment report GRC tool PDF export with sign-off
Vendor risk assessments Vendor management tool Export assessment records
Penetration test reports Security vendor PDF reports with remediation tracking
Vulnerability scan results Scanner (Qualys, Nessus, etc.) Automated export, monthly

CC4: Monitoring Activities

Evidence Source Collection Method
SIEM dashboards and alert configs Datadog / Splunk / CloudWatch Screenshot + config export
Uptime monitoring evidence Pingdom / Datadog / UptimeRobot Monthly uptime reports
Log retention configuration Cloud provider console Config export / IaC snippet
Anomaly detection rules SIEM / monitoring tool Rule export with change log

CC5: Control Activities

Evidence Source Collection Method
Access control matrix IdP / IAM console Export user-role mappings
MFA enforcement evidence IdP admin console Policy config screenshot
Firewall / security group rules Cloud console / IaC terraform state or console export
Encryption at rest configuration Cloud console / IaC Config export showing encryption enabled
Encryption in transit (TLS) Load balancer / CDN config Certificate + config export

CC6: Logical and Physical Access Controls

Evidence Source Collection Method
User access reviews (quarterly) IdP + spreadsheet Review meeting notes + updated access list
Terminated user deprovisioning IdP audit log Export showing timely deactivation
SSH key / credential rotation logs Secrets manager Rotation event logs
Physical access logs (if applicable) Building management Badge access reports

CC7: System Operations

Evidence Source Collection Method
Change management records Jira / GitHub PRs Export merged PRs with approvals
CI/CD pipeline configuration GitHub Actions / CircleCI Config file export from repo
Deployment approval process PR review settings Branch protection rule screenshots
Incident response logs PagerDuty / Opsgenie Incident timeline exports
Backup configuration and test results Cloud console / IaC Backup policy + restore test logs

CC8: Change Management

Evidence Source Collection Method
PR review requirements GitHub / GitLab settings Branch protection config
Code review evidence GitHub PR history Export PRs with review comments
Release notes / changelogs Repo CHANGELOG.md with version history
Rollback procedures Runbook Documented procedure with test evidence

CC9: Risk Mitigation

Evidence Source Collection Method
Business continuity plan Policy repo Document with annual review evidence
Disaster recovery test results DR runbook Test execution logs + results
Insurance certificates Finance / legal Current certificate copies
Sub-processor agreements Legal / contract management Signed DPAs + vendor list

A — Availability (If In Scope)

Evidence Source Collection Method
SLA definitions and monitoring Product docs + monitoring SLA doc + uptime dashboard exports
Capacity planning documentation Architecture docs Quarterly capacity review notes
Auto-scaling configuration Cloud console / IaC Config export
Incident response SLA adherence PagerDuty / incident tracker Response time reports
Redundancy / failover configuration Cloud architecture Architecture diagram + failover test logs

PI — Processing Integrity (If In Scope)

Evidence Source Collection Method
Data validation rules Application code / config Code snippets + test results
QA / testing procedures CI/CD pipeline Test suite config + pass/fail reports
Error handling and correction procedures Runbook / code Error handling docs + incident examples
Data reconciliation reports Application logs / reports Monthly reconciliation output

C — Confidentiality (If In Scope)

Evidence Source Collection Method
Data classification policy Policy repo Document with review history
NDA / confidentiality agreements Legal / HR Signed agreement copies
Data retention and disposal policy Policy repo Policy doc + disposal logs
DLP tool configuration DLP tool admin Config export + alert samples

P — Privacy (If In Scope)

Evidence Source Collection Method
Privacy policy (public) Website URL + version history
Data processing agreements Legal Signed DPAs
Consent management records CMP / application Consent log exports
Data subject request procedures Policy repo / ticketing Procedure doc + DSR ticket samples
Privacy impact assessments GRC tool / docs PIA reports for high-risk processing

Automation Scripts

When the user's stack is identified, generate shell scripts for automated evidence collection:

AWS Evidence Collection (example)

#!/bin/bash
# SOC2 Evidence Collector — AWS
# Generated by AfrexAI SOC2 Evidence Collector skill
set -euo pipefail

EVIDENCE_DIR="soc2-evidence/$(date +%Y-%m-%d)"
mkdir -p "$EVIDENCE_DIR"/{iam,network,encryption,logging,compute}

echo "=== CC5: Access Controls ==="
aws iam get-account-summary > "$EVIDENCE_DIR/iam/account-summary.json"
aws iam generate-credential-report && sleep 5
aws iam get-credential-report --output text --query Content | base64 -d > "$EVIDENCE_DIR/iam/credential-report.csv"
aws iam list-users --output json > "$EVIDENCE_DIR/iam/users.json"
aws iam list-policies --scope Local --output json > "$EVIDENCE_DIR/iam/custom-policies.json"

echo "=== CC5: Encryption at Rest ==="
aws rds describe-db-instances --query 'DBInstances[*].{ID:DBInstanceIdentifier,Encrypted:StorageEncrypted,KmsKey:KmsKeyId}' > "$EVIDENCE_DIR/encryption/rds-encryption.json"
aws s3api list-buckets --query 'Buckets[*].Name' --output text | tr '	' '\
' | while read bucket; do
  aws s3api get-bucket-encryption --bucket "$bucket" >> "$EVIDENCE_DIR/encryption/s3-encryption.json" 2>/dev/null || echo "{\"bucket\":\"$bucket\",\"encryption\":\"NONE\"}" >> "$EVIDENCE_DIR/encryption/s3-encryption.json"
done

echo "=== CC4: Logging ==="
aws cloudtrail describe-trails > "$EVIDENCE_DIR/logging/cloudtrail-config.json"
aws cloudwatch describe-alarms --state-value ALARM > "$EVIDENCE_DIR/logging/active-alarms.json"

echo "=== CC5: Network Security ==="
aws ec2 describe-security-groups > "$EVIDENCE_DIR/network/security-groups.json"
aws ec2 describe-vpcs > "$EVIDENCE_DIR/network/vpcs.json"

echo "=== CC6: MFA Status ==="
aws iam list-virtual-mfa-devices > "$EVIDENCE_DIR/iam/mfa-devices.json"

echo "Evidence collected in $EVIDENCE_DIR"
echo "Review and redact sensitive values before sharing with auditors."

GitHub Evidence Collection (example)

#!/bin/bash
# SOC2 Evidence Collector — GitHub
set -euo pipefail

ORG="${1:?Usage: $0 \x3Cgithub-org>}"
EVIDENCE_DIR="soc2-evidence/$(date +%Y-%m-%d)/github"
mkdir -p "$EVIDENCE_DIR"

echo "=== CC8: Branch Protection ==="
gh api "/orgs/$ORG/repos" --paginate --jq '.[].name' | while read repo; do
  gh api "/repos/$ORG/$repo/branches/main/protection" 2>/dev/null > "$EVIDENCE_DIR/${repo}-branch-protection.json" || true
done

echo "=== CC7: Recent Deployments ==="
gh api "/orgs/$ORG/repos" --paginate --jq '.[].name' | head -10 | while read repo; do
  gh api "/repos/$ORG/$repo/deployments?per_page=10" > "$EVIDENCE_DIR/${repo}-deployments.json" 2>/dev/null || true
done

echo "=== CC8: PR Review Evidence ==="
gh api "/orgs/$ORG/repos" --paginate --jq '.[].name' | head -10 | while read repo; do
  gh pr list --repo "$ORG/$repo" --state merged --limit 20 --json number,title,mergedAt,reviewDecision > "$EVIDENCE_DIR/${repo}-merged-prs.json" 2>/dev/null || true
done

echo "=== CC5: Org Security Settings ==="
gh api "/orgs/$ORG" --jq '{two_factor_requirement: .two_factor_requirement_enabled, default_permissions: .default_repository_permission}' > "$EVIDENCE_DIR/org-security.json"

echo "Evidence collected in $EVIDENCE_DIR"

Output Format

Generate a structured evidence package:

soc2-evidence/
├── README.md                    # Overview, scope, period, auditor info
├── evidence-matrix.md           # Full checklist with status (collected/pending/N-A)
├── collection-scripts/
│   ├── collect-aws.sh
│   ├── collect-github.sh
│   ├── collect-idp.sh
│   └── collect-monitoring.sh
├── gap-analysis.md              # Missing evidence + remediation steps
└── schedule.md                  # Evidence collection calendar (what to refresh when)

evidence-matrix.md Format

| # | Control | Evidence | Status | Source | Last Collected | Notes |
|---|---------|----------|--------|--------|---------------|-------|
| CC1.1 | Org chart | org-chart-2026-Q1.pdf | ✅ Collected | HR export | 2026-01-15 | |
| CC5.3 | MFA enforcement | mfa-config.json | ✅ Automated | IdP API | 2026-03-17 | Script: collect-idp.sh |
| CC3.2 | Pen test report | — | ⏳ Pending | External vendor | — | Due 2026-04-01 |

Workflow

  1. Gather inputs (audit type, scope, stack, team size)
  2. Generate the full evidence matrix for in-scope criteria
  3. Mark known evidence sources based on their stack
  4. Generate collection scripts for automated gathering
  5. Identify gaps and generate remediation recommendations
  6. Create an evidence collection schedule (daily/weekly/monthly/quarterly)
  7. Output the complete evidence package

Tips for Users

  • Start 3-6 months before audit: evidence gaps take time to fill
  • Automate early: scripts that run monthly save panic before audit
  • Version everything: auditors love seeing change history
  • Don't fake it: missing evidence is better than fabricated evidence
  • Continuous > point-in-time: Type II requires sustained evidence over the audit period
  • Tag evidence: use consistent naming so auditors can self-serve

AfrexAI Note

This skill generates the framework and automation scaffolding. For hands-on SOC2 audit preparation with managed AI agents handling continuous evidence collection, monitoring, and auditor coordination — that's what AfrexAI's AI-as-a-Service delivers. Contact us at [email protected].

安全使用建议
This skill can legitimately help prepare SOC2 evidence, but proceed with caution: - Ask the agent (before providing anything) exactly how it will collect credentials and where it will store or transmit collected evidence. Do not paste sensitive credentials into chat unless you understand and trust the destination. - Prefer issuing temporary, least-privilege, read-only API tokens (for AWS/GCP/Azure, GitHub, and your IdP) and set short expirations. Never supply root or full-admin credentials. - Require the agent to produce scripts first and review them manually before execution. Run any generated scripts in an isolated environment (sandbox or dedicated machine) and inspect network activity if possible. - Confirm the skill will not upload evidence packages to external endpoints you do not control; ask for explicit filenames/paths and retention policies. - If you plan to allow autonomous agent invocation, restrict that until you’ve tested the workflow manually; consider disabling autonomous runs for this skill. Given the skill is instruction-only and the package contains no code, the absence of scan findings is not a guarantee of safety — verify credential handling and review outputs before using in production.
功能分析
Type: OpenClaw Skill Name: afrexai-soc2-evidence-collector Version: 1.0.0 The skill bundle provides a framework and automation scripts for SOC2 evidence collection. The included Bash scripts for AWS and GitHub (found in SKILL.md) use standard CLI tools to perform read-only discovery of security configurations and save them to a local directory for audit purposes. No evidence of data exfiltration, malicious execution, or prompt injection was found; the behavior is entirely consistent with the stated purpose of compliance auditing.
能力评估
Purpose & Capability
The name/description match the content: the skill aims to produce evidence checklists and automated collection scripts for cloud, GitHub, and IdP platforms. That capability is coherent with the stated purpose. However, generating runnable collection scripts for multiple platforms inherently requires credentials, API tokens or console access that are not described in the metadata (no required env vars or config paths). The absence of any declared credential requirements is a notable omission but could be explained if the agent always asks interactively for credentials or instructs the user to run scripts locally.
Instruction Scope
The SKILL.md instructs the agent to generate scripts and instructions to export logs, IAM mappings, terraform state, console configs, HR exports, calendar screenshots, and other sensitive artifacts across cloud providers and IdPs. Those instructions imply collection of highly sensitive data (credentials, logs, PII). The document does not explicitly constrain what the agent may ask for or where collected evidence may be sent; it also does not require explicit user approval steps before creating or transmitting evidence. This open scope increases the risk the agent might request or assemble sensitive artifacts in ways the user didn't expect.
Install Mechanism
This is an instruction-only skill with no install spec and no bundled code — low disk footprint and no remote install URLs. That minimizes supply-chain risk from the package itself.
Credentials
The skill will need access to cloud consoles, IdPs, GitHub, HR systems, and possibly on-prem systems to collect evidence, but the registry metadata declares no required environment variables, credentials, or config paths. That mismatch means the skill either expects interactive credential entry, will produce scripts that require credentials, or will instruct the user to run commands themselves — the SKILL.md does not make the handling, scoping (read-only vs. admin), or lifetime (temporary vs. permanent) of secrets explicit. Requesting broad access to many services without specifying least-privilege guidance is disproportionate.
Persistence & Privilege
The skill is not marked always:true and does not request any system-level persistence. It is user-invocable and allows model invocation (normal default). There is no evidence in the package of attempts to modify other skills or system-wide agent settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install afrexai-soc2-evidence-collector
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /afrexai-soc2-evidence-collector 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of SOC2 Evidence Collector by AfrexAI. - Generate comprehensive SOC2 evidence collection checklists for all 5 Trust Service Criteria (Security, Availability, Processing Integrity, Confidentiality, Privacy). - Automate evidence gathering scripts and workflows tailored for SOC2 Type I and Type II audits. - Produce audit-ready evidence packages to streamline compliance processes. - Includes detailed guidance on required inputs, evidence categories, and recommended collection methods. - Useful for audit preparations, continuous compliance, and evidence automation.
元数据
Slug afrexai-soc2-evidence-collector
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Soc2 Evidence Collector 是什么?

Generate SOC2 evidence collection checklists, automate evidence gathering scripts, and produce audit-ready evidence packages. Covers all 5 Trust Service Crit... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 225 次。

如何安装 Soc2 Evidence Collector?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install afrexai-soc2-evidence-collector」即可一键安装,无需额外配置。

Soc2 Evidence Collector 是免费的吗?

是的,Soc2 Evidence Collector 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Soc2 Evidence Collector 支持哪些平台?

Soc2 Evidence Collector 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Soc2 Evidence Collector?

由 afrexai-cto(@afrexai-cto)开发并维护,当前版本 v1.0.0。

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