Code attack surface
Entry points an attacker can reach.
- REST / GraphQL / gRPC endpoints
- File upload handlers
- Authn/authz gates and missing checks
- User input sinks (queries, commands, templating)
AGENTIC AI
Pre‑VAPT Intelligence • Code + Cloud Attack Surface
Complete attack surface intelligence — before VAPT begins.
Xhield automatically discovers your exposed endpoints, cloud resources, and misconfigurations, then correlates code → infrastructure → data stores to produce a VAPT‑ready scope, prioritized fixes, and audit‑friendly reporting.
What Xhield discovers (before VAPT)
Reconnaissance and asset discovery consume ~30–40% of VAPT time. Xhield automates this phase across code + cloud so external testers can spend time on higher-value testing.
Cloud exposure
Internet-facing assets and risky configuration.
- Public IPs, load balancers, gateways
- Open security groups (0.0.0.0/0)
- Public buckets, public databases
- Encryption, logging, backup posture
Code ↔ cloud correlation
Where “code findings” become exploitable.
- Endpoint → service → datastore mapping
- Blast radius per endpoint
- Exploitability-aware prioritisation
- VAPT-ready testing scope definition
Agentic AI workflow
Multiple specialised agents collaborate: one extracts code entry points, another scans cloud posture, a correlation agent connects them, then risk + reporting agents generate a VAPT-ready plan.
Code Analyzer Agent
Find endpoints, parameters, auth, and risky sinks.
Cloud Scanner Agent
Discover internet exposure, IAM, network, storage misconfig.
Correlation Agent
Map code endpoints to live infrastructure and data flows.
Risk Scoring Agent
Rank findings by exposure + exploitability + sensitivity.
Reporting Agent
Generate VAPT-ready scope, exports, and executive summaries.
Continuous Monitoring (optional)
Detect drift and newly exposed assets between VAPT cycles.
Next step
Share your cloud(s), repositories, and upcoming VAPT timeline. We’ll propose an assessment scope and a fast path to reduce critical findings before external testing.