Nemesis: the workspace behind our deepest analysis

Nemesis is an advanced security operations platform centered on a consultant-directed investigation loop. It continuously generates and executes investigation tasks with specialized agents, incorporates evidence from static analysis and runtime testing, and compounds results into findings, test plans, and reports.

One workspace, from evidence to deliverables

Security teams usually stitch together separate tools for code analysis, finding triage, reporting, and collaboration. Nemesis consolidates those workflows into one platform with shared context and persistent run history.

Engagement Workspace

Each engagement gets a scoped workspace where consultants upload code, documentation, and flow recordings. Everything stays organized and accessible to the team throughout the assessment.

Autonomous Investigation Loop

Nemesis orchestrates iterative investigation cycles: generate tasks, execute agent investigations, consolidate findings, and spawn follow-up work based on new evidence.

Specialist Review Agents

Code-review-equipped agents investigate targeted hypotheses, return structured evidence, and feed the next loop. Consultants steer priorities and approve outcomes.

Deep Research and Threat Modeling

AI-assisted research synthesis grounded in workspace evidence, plus OWASP Threat Dragon model generation and import. Findings, research, and notes compound into structured risk artifacts.

Test Plan Generation

Nemesis generates structured security test plans from findings, research, and engagement context. Consultants refine through an interactive Q&A loop and export finalized plans.

Report Drafting

Pentest-style report generation from cross-feature evidence with live editing during drafting. Consultants control every conclusion before export.

Ten engines, one normalized output

Nemesis integrates ten static analysis tools covering code quality, dependency vulnerabilities, secrets detection, and infrastructure-as-code scanning. Run them individually or launch the full suite in parallel.

Each engine's findings go through an LLM-assisted triage pipeline that classifies results as true positives or false positives, applies reconciliation passes for consistency, and produces standardized outputs that feed directly into findings, test plans, and reports.

Code and dependency scanning

Snyk Open Source, Snyk Code, Semgrep, Bandit, DevSkim, ESLint, PVS-Studio, and Detekt.

Secrets detection

Gitleaks scans repositories for exposed credentials, API keys, and other sensitive data.

Infrastructure as code

Consolidated IaC scanning via Checkov, Kubescape, Hadolint, and Helm Lint for container and Kubernetes configuration review.

Those standardized results give Nemesis a clean starting point for deeper custom investigation. The orchestrator turns validated signals into investigative items, assigns them to code-review-equipped agents, and continues iterating as new evidence is uncovered.

From broad signal generation to targeted custom investigation

Nemesis does not stop at surfacing candidate issues. Its orchestrator uses findings from static analysis, documentation, prior notes, and other engagement evidence to generate investigative items, launch specialist review agents, consolidate new evidence, and continue the loop until the most important questions are resolved.

This is where the deeper analysis happens: not just identifying possible problems, but following lines of inquiry, validating exploitability, refining hypotheses, and feeding each round of findings into the next.

The consultant stays in the loop

Nemesis proposes. The consultant decides. Nothing ships to a client without expert review and sign-off.

nemesis > orchestrator start --engagement acme-webapp
[*] Source artifacts indexed. Static analysis baseline complete.
[*] 12 validated findings and 9 investigation candidates generated.
[*] Launching code review agents against highest-priority paths...
[*] Agent review complete. 4 new investigative items created.
[*] Loop 2 started with follow-up hypotheses and expanded evidence.
[+] 3 critical findings confirmed with supporting code-path analysis.
[*] Generating test plan and report draft from validated results...

Consultants drive it. Nemesis handles the grind.

Setting scope

Every engagement starts with a human defining what to test, how to test it, and what matters most. Nemesis executes within those boundaries.

Approving pivots

When the investigation loop uncovers new leads or wants to pursue deeper analysis paths, consultants decide which directions to follow. Nothing runs without human approval.

Validating findings

Every finding that reaches a client has been reviewed, validated, and contextualized by a human expert. Nemesis surfaces candidates; consultants make the call.

Signing off deliverables

Reports, test plans, and risk assessments carry a consultant's judgment, not just a tool's output. Nemesis drafts; humans verify and deliver.

Runs anywhere. Data stays with you.

Containerized

Nemesis runs as containerized services that deploy to any infrastructure: on-prem, cloud, or hybrid. No vendor lock-in.

Any cloud

AWS, Azure, GCP, or your own data center. Nemesis adapts to your environment rather than forcing you into ours.

Any LLM provider

Nemesis routes AI workloads through a centralized gateway supporting OpenAI, Azure OpenAI, Gemini, DeepInfra, Baseten, and AWS Bedrock. Use the provider that fits your requirements.

Data stays in your environment

Client source code and findings never leave the deployment environment. Cloud service boundaries are protected with mTLS. Your data, your infrastructure, your control.

Want to see Nemesis in action?

Nemesis powers our AI security assessments and code analysis and application testing engagements. Talk to us about how it works.

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