Solutions

AI Code Assistants

Speed up reviews, tests, and migrations without letting an unchecked agent drop databases or leak IP.

Code copilots now autocomplete entire services, explain legacy payment flows, and even run toolchains. Without strong scopes they hallucinate packages, cite old APIs, or execute destructive commands while believing they are helpful.

Typical deployments

IDE extensions that turn natural-language tickets into functions, unit tests, or refactors with inline citations.
Secure chat interfaces that answer “how does this accounting service work?” by reading private repos and design docs.
Governed autonomous agents that prepare schema migrations or pull requests in staging environments for human review.

Incidents we prevent

Field report

Replit “vibe” wiped a production database

A startup testing Replit’s vibe agent watched it ignore a code freeze, run destructive commands, delete prod data, and fabricate fake telemetry—underscoring how fast an unsandboxed agent can go off-script.

PCMag Cybernews

Field report

Hallucinated or vulnerable code shipped to prod

A Communications of the ACM study found more than a third of Copilot’s outputs contained CWEs, and engineers keep catching copilots inventing non-existent packages or reviving deprecated APIs in mockable stacks.

Communications of the ACM

Field report

Copyright fights and proprietary leaks

GitHub, Microsoft, and OpenAI are fighting lawsuits over copilots regurgitating licensed code, while Samsung and Amazon saw public models echo internal snippets after developers pasted them into prompts.

The Verge Reuters

How General Analysis helps

General Analysis

AI Runtime Protection & Observability

Wrap IDEs, CLIs, and DevOps agents with command allowlists, human-in-the-loop approvals, and automated lint/SAST/test hooks so dangerous suggestions never reach git or production without review.

General Analysis

AI Red Teaming

Stress-test prompts and tools with jailbreaks, bogus dependencies, and social-engineered tasks to expose how the copilot behaves under pressure—and fix it before engineers rely on it.

General Analysis

AI Security Asset Management

Maintain a real-time inventory of models, embeddings, and knowledge bases feeding the copilot, enforce on-prem or VPC deployments, and run license/PII scans so nothing leaves your tenancy.

Playbook highlights

Gives assistants read-only mirrors of repos, artifact stores, and deployment targets so they can propose changes without the ability to run commands or drop databases by accident.
Couples every suggestion with automated unit tests, static/security scans, and hallucination scoring; low-confidence or insecure code is flagged before developers accept it.
AI Security Asset Management inspects training corpora and context windows for proprietary logic, secrets, or GPL-incompatible snippets so the assistant never leaks IP.
AI Red Teaming hammers prompts, toolchains, and MCP workflows with adversarial test cases to prove guardrails hold before assistants reach production.

FAQ

Runtime Protection can require static analysis, generated unit tests, and citations before an answer is shown. Anything low-confidence is automatically routed to peer review so the AI behaves like a junior engineer, not an unchecked committer.

Yes—retrieval layers pull sanctioned snippets, ADRs, and runbooks without copying repos outside your VPC. If guidance drifts, admins can push new system prompts or content syncs so the assistant reflects the current architecture.

Asset Management keeps prompts and completions encrypted in your tenancy, redacts secrets, and runs similarity checks. If outputs resemble licensed code, the copilot regenerates them or flags the human reviewer.

No. High-risk commands require human approval by default, and you can force MFA, change windows, or staged rollouts for anything beyond read-only analysis so a vibe-style incident is impossible.

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