Home / Capabilities

Capabilities built for secure delivery, measurable compliance, and responsible AI.

We combine hands-on engineering with advisory clarity—helping organizations move from fragmented controls and manual evidence to scalable guardrails, reusable architectures, and operational visibility.

Security Operations, SIEM & Detection Engineering

SIEM and observability engineering across Splunk, ArcSight, Elastic Stack, Panther, and related telemetry platforms.
Telemetry onboarding, parsing, normalization, key-value mapping, enrichment, and dashboard/report design.
SOC modernization, incident workflows, runbooks, playbooks, detection tuning, and executive reporting.
Threat intelligence enrichment, log correlation, forensic collection support, and malware/threat-analysis workflows.

Cloud Security, Zero Trust & Platform Engineering

AWS, Azure, and GCP security architecture with identity, secrets, encryption, segmentation, and telemetry controls.
IaC and CI/CD using AWS CDK, CloudFormation, Terraform-style patterns, Docker, Python, Bash, and repeatable deployment pipelines.
Secure data-lake and cross-account integration patterns for monitoring and evidence collection.
Zero-trust-aligned patterns for privileged access, federation, service identities, and guardrail enforcement.

Compliance Automation, RMF / ATO & Privacy

RMF, ATO, FedRAMP, HIPAA, FISMA, POA&M, audit evidence generation, and continuous monitoring support.
MITRE SAF-based assessment automation, control validation, and repeatable artifact creation for federal programs.
Privacy engineering, data protection design, and secure handling of regulated and mission data.
Documentation support spanning SSPs, plans, runbooks, evidence maps, gap analyses, and stakeholder-ready reporting.

AI Assurance, Guardrails & Secure Integration

Responsible AI adoption for small models, large models, and agentic workflows.
AI governance, model and data privacy reviews, prompt-injection defenses, and secure RAG patterns.
Guardrails for agents, model APIs, non-human identities, tool access, and sensitive-data controls.
Support for secure AI integration into engineering, analytics, and operational workflows.

AI security focus areas

What we watch for in modern model and agent deployments.

Our AI assurance work is designed around practical implementation concerns, not just policy language.

Model, data, and retrieval risks

Prompt injection and unsafe retrieval behavior
Sensitive data disclosure and tenant-isolation failures
Data poisoning, provenance, and supply-chain integrity
Secure evaluation, drift, and monitoring patterns

Agent and integration controls

Tool allow-lists, scoped credentials, and approval gates
Secret handling, key lifecycle, and non-human identity controls
Least-privilege access for model APIs and downstream systems
Logging, containment, and human-in-the-loop escalation

AI management lens

Our emerging AI offerings are informed by current graduate work in Georgetown’s AI Management program, including course areas such as AI Governance & Compliance, AI Security & Data Privacy, AI Applications Integration, Data Engineering for AI, Developing AI Solutions, and AI System Design & Architecture.

Tools & frameworks

Selected platforms, frameworks, and delivery assets.

We tailor the stack to the mission, but these are the ecosystems and standards most commonly represented in our work.

Platforms and tools

Splunk ArcSight Elastic Stack Panther AWS Azure GCP AWS CDK CloudFormation Docker Jenkins Ansible Palo Alto Imperva Nessus Tenable Security Center Python Ruby C# Java

Frameworks and methods

NIST 800-53 RMF / ATO FISMA FedRAMP HIPAA SOC 2 PCI DSS CIS STIG MITRE ATT&CK MITRE SAF AI RMF concepts Zero Trust CDM POA&M

Chameleon’s capability statement and SBA narrative are included in this site package for direct download and reuse.

Download the capability package.

Use the PDF capability statement for outreach, opportunity responses, or procurement discussions.

Capability Statement PDF SBA Narrative TXT