7.0 KiB
7.0 KiB
id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack
| id | title | category | status | canonical_id | aliases | duplicate_of | source_trust_level | confidence_score | verification_status | tags | raw_sources | last_reinforced | github_commit | tech_stack | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wiki-2026-0508-deepcode-ai | DeepCode AI (Snyk Code) | 10_Wiki/Topics | verified | self |
|
none | B | 0.85 | applied |
|
2026-05-10 | pending |
|
DeepCode AI (Snyk Code)
매 한 줄
"매 LLM 의 X — 매 symbolic + neural 의 결합". 매 25M+ data flow + 매 19+ language. 매 interfile analysis. 매 commit-based 의 verified fix pattern. 매 modern hybrid 의 example (vs LLM-only Corgea).
매 핵심 differentiator
Hybrid AI (vs LLM-only)
- 매 symbolic reasoning + 매 NN.
- 매 semantic representation 의 build.
- 매 hallucination ↓.
- 매 interpretable.
Interfile dataflow
- 매 file boundary 의 cross.
- 매 multi-module vulnerability 의 catch.
Commit-based fix pattern
- 매 OSS 의 actual fix commits 의 학습.
- 매 verified pattern.
- 매 LLM hallucination 의 avoid.
매 history
- 매 2017 ETH spinoff (DeepCode).
- 매 2020 Snyk 의 acquire.
- 매 2024 DeepCode AI Fix.
매 Snyk 의 stack
- Snyk Code (DeepCode-powered SAST).
- Snyk Open Source (SCA).
- Snyk Container (image scan).
- Snyk IaC (Terraform / K8s).
매 vs alternative
| Tool | Approach | Strength |
|---|---|---|
| Snyk Code (DeepCode) | Hybrid neuro-symbolic | Verified fix + low FP |
| Corgea | LLM-native | Business logic + autofix |
| Semgrep | Pattern + custom | Speed + control |
| SonarQube | Rule-based + AI | Quality gate |
| GitHub Advanced | Code scanning + Copilot Autofix | GitHub integration |
매 limitation
- 매 LLM-native 의 emerging features (Corgea) 의 less.
- 매 enterprise SaaS pricing.
- 매 language-specific depth varies.
💻 패턴 (응용 — Snyk integration)
CLI scan
npm install -g snyk
snyk auth
snyk code test # 매 SAST
snyk code test --json # 매 JSON output
snyk code test --severity-threshold=high
CI integration
- name: Snyk Code
uses: snyk/actions/node@master
env: { SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }} }
with:
command: code test
args: --severity-threshold=high --sarif-file-output=snyk-code.sarif
- name: Upload SARIF
uses: github/codeql-action/upload-sarif@v3
with: { sarif_file: snyk-code.sarif }
IDE integration
- VS Code: Snyk Security extension.
- IntelliJ / WebStorm: Snyk plugin.
- 매 inline 의 finding + fix 의 click.
DeepCode AI Fix workflow
1. Vulnerability detected (e.g., SQL injection).
2. AI Fix 의 verified pattern 의 retrieve.
3. PR comment 의 diff 의 propose.
4. Developer 의 review + merge.
5. Snyk 의 re-test 의 confirm fix.
Multi-tool layered security
security_pipeline:
pre_commit:
- gitleaks # 매 secret
pr:
- snyk_code # 매 SAST (DeepCode)
- snyk_open_source # 매 SCA (CVE)
- semgrep # 매 custom rule
- corgea # 매 LLM-native (optional, parallel)
pre_deploy:
- snyk_container # 매 image
- cosign # 매 sign
runtime:
- falco
Custom rule (Snyk + Semgrep complementary)
# 매 .snyk policy
ignore:
'SNYK-CC-K8S-1':
- '*':
reason: 'Internal dev cluster — non-prod'
expires: '2026-12-31T00:00:00Z'
# 매 semgrep for org-specific
rules:
- id: internal-deprecated-api
pattern: oldClient.deprecatedMethod(...)
message: Use newClient instead.
severity: WARNING
Vulnerability triage
def triage_findings(snyk_findings):
triaged = []
for f in snyk_findings:
priority = (
f['severity_score'] *
f['exploit_maturity_factor'] * # 매 0.5-2
f['reachability_factor'] # 매 0.3-1.5
)
triaged.append({
**f,
'priority': priority,
'sla_hours': sla_for_severity(f['severity']),
})
return sorted(triaged, key=lambda x: -x['priority'])
Auto-fix verification
def verify_fix(original_code, ai_proposed_fix):
# 매 1. syntax check
if not parses_correctly(ai_proposed_fix): return 'invalid syntax'
# 매 2. test still passes
if not run_tests(ai_proposed_fix): return 'tests fail'
# 매 3. vulnerability resolved
if scan(ai_proposed_fix).has_vuln: return 'vuln remains'
# 매 4. no new vuln introduced
new_vulns = set(scan(ai_proposed_fix).vulns) - set(scan(original_code).vulns)
if new_vulns: return f'introduces new: {new_vulns}'
return 'verified'
SARIF (standard output)
import json
def parse_sarif(sarif_file):
with open(sarif_file) as f:
data = json.load(f)
findings = []
for run in data['runs']:
for result in run['results']:
findings.append({
'rule': result['ruleId'],
'severity': result['level'],
'message': result['message']['text'],
'file': result['locations'][0]['physicalLocation']['artifactLocation']['uri'],
'line': result['locations'][0]['physicalLocation']['region']['startLine'],
})
return findings
Suppress false positives
// 매 Snyk 의 inline ignore
function safe_html(input) {
// snyk-ignore: javascript/xss — 매 input 의 sanitized at boundary
return `<div>${input}</div>`;
}
매 결정 기준
| 상황 | Tool |
|---|---|
| Mid-large + budget | Snyk Code (DeepCode) |
| AI-native focus | Corgea |
| Custom rules speed | Semgrep |
| Open-source self-host | SemGrep |
| GitHub native | GitHub Advanced Security |
| Enterprise compliance | Veracode / Checkmarx |
기본값: 매 Snyk + Semgrep complementary.
🔗 Graph
- 부모: SAST · DevSecOps
- 변형: Snyk-Code · Symbolic-AI · Hybrid-AI · Neuro-Symbolic-AI
- 응용: Corgea · Semgrep · SonarQube · CI_CD 파이프라인 및 IDE 통합 보안
- Adjacent: AI 코드 리뷰 및 보안 취약점 점검(DevSecOps) · Custom-ESLint-Rules-Development · CodeScene · AI 생성 코드 검증(AI Code Assurance)
🤖 LLM 활용
언제: 매 enterprise SAST. 매 multi-language. 매 verified autofix. 언제 X: 매 budget-tight (Semgrep). 매 air-gapped.
❌ 안티패턴
- Single tool: 매 layered defense X.
- No triage: 매 alert fatigue.
- AI Fix 의 blind merge: 매 verify 의 still 필요.
- No SARIF integration: 매 dashboard 의 single source X.
🧪 검증 / 중복
- Verified (Snyk docs, DeepCode papers, ETH spinoff history).
- 신뢰도 B.
- Related: Corgea · CI_CD 파이프라인 및 IDE 통합 보안 · Custom-ESLint-Rules-Development · CodeScene.
🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — neuro-symbolic + 매 CI / SARIF / triage / verify code |