A full-stack security portfolio — one team behind all of it

SkandaShield tests web applications, mobile apps, APIs, microservices, cloud infrastructure, and network perimeters the way a real attacker would — chaining smaller weaknesses into a proven path to sensitive data or critical systems. This extends to data pipeline VAPT: ingestion points, ETL processes, storage layers, and ML/AI endpoints, which are frequently left out of conventional scopes.

What we test, by surface. Web & API — injection (SQL, NoSQL, command), broken access control, BOLA/BFLA, authentication and session flaws, SSRF. Mobile — insecure local storage, weak certificate pinning, reverse-engineerable business logic. Cloud — IAM over-permissioning, public storage exposure, lateral-movement paths between accounts and services. Network — segmentation gaps, Active Directory attack paths, legacy protocol exposure.

Every engagement is scoped against your architecture first, so testing time goes toward the components that actually carry risk rather than a generic checklist.

Available either as a one-time assessment ahead of a release or audit, or as an ongoing testing program with the SkandaShield platform layered on top for continuous coverage between engagements. Most web, mobile, or API engagements run one to three weeks depending on scope; cloud and network engagements are scoped individually against the size of the environment.

Standards & frameworks: OWASP Top 10 · NIST SP 800-115 · CIS Benchmarks · MITRE ATT&CK

Testing of hardware, embedded, and cyber-physical systems across firmware, interfaces, radio protocols, and communication stacks — the layer most application-focused security vendors don't touch.

What we look for. Hardcoded or default credentials, insecure bootloaders and lack of secure boot, unauthenticated or unencrypted over-the-air update mechanisms, exposed debug interfaces left enabled in production units, weak or absent pairing/authentication on wireless links, and side-channel exposure on cryptographic operations.

Engagements run as scoped lab or on-site work, typically over one to four weeks depending on device complexity and the number of interfaces in scope.

Standards & frameworks: OWASP IoT practices · FDA Premarket Cybersecurity guidance (medical devices) · ISO 26262-1:2018 · ISO/SAE 21434 · UNECE R155 & R156 (automotive)

Securing an AI system means covering it end to end: the data that trains it, how the model itself holds up under attack, and the way it behaves once it's live. SkandaShield delivers all three as a single engagement, not three separate vendor relationships. Coverage spans proprietary and open-weight LLMs, classical ML classifiers, computer-vision models, and multi-agent systems, in any hosting framework.

Data & pipeline governance. Provenance and lineage tracking, consent and policy-as-code, secure feature stores, watermarking, data immutability, and a tamper-evident AI Bill of Materials (AIBOM) — the record you need when a regulator or customer asks where a model's training data actually came from. We specifically test for training-data poisoning, membership-inference exposure, and unauthorised model extraction.

Model & application testing. LLM-specific testing layered on top of conventional web and API assessment, because static and dynamic scanning alone don't surface adversarial-AI risk. This includes benchmarking against real-world jailbreak and abuse techniques — unauthorised data extraction, disallowed content generation, actions taken on another user's behalf — plus deeper model-level attacks: extraction, attribute inference, model inversion, and evasion. Covers any LLM family, whether embedded in a web application or called directly.

Agentic & MCP-specific testing. Agent frameworks and the Model Context Protocol (MCP) are now the dominant way LLMs reach tools and data — and the fastest-moving attack surface in the industry, with dozens of CVEs disclosed against MCP server implementations in 2026 alone. We test specifically for the risk classes named in the current OWASP Top 10 for Agentic Applications (ASI01–ASI10): agent goal hijacking, tool misuse, identity and privilege abuse, agentic supply-chain compromise, unexpected code execution, memory and context poisoning, insecure inter-agent communication, cascading multi-agent failures, human-agent trust exploitation, and rogue agents. On the protocol layer specifically, testing covers the confused-deputy pattern, token passthrough, session hijacking, tool poisoning and "rug-pull" tool redefinition, and SSRF via metadata endpoints — the exact classes behind the MCP CVEs disclosed this year — plus supply-chain risk in third-party agent skill and plugin marketplaces, per the OWASP Agentic Skills Top 10.

Runtime defence & SOC. Agent governance policies, AI firewall guardrails, prompt- and jailbreak-detection, AI security posture management (AI-SPM), curated detection packs, SOC runbooks, and purple-team exercises against your own agents before they're relied on in production.

Available as a one-time assessment or as continuous testing that keeps pace as models, prompts, and agent behaviour change — a point-in-time report alone can't catch what shifts between releases.

Already running AI-driven security tooling of your own? SkandaShield's engineers will validate its output too — reproducing findings in your environment, confirming real severity, and cutting through false positives — vendor-neutral, whether the results come from our testing or yours. Same principle as our VAPT work: AI accelerates the work, it doesn't replace the judgment.

Standards & frameworks: OWASP Top 10 for Agentic Applications (ASI01–ASI10) · OWASP MCP Top 10 · OWASP Agentic Skills Top 10 · OWASP LLM Top 10 · MITRE ATLAS · NIST AI RMF (AI 600-1 GenAI Profile) · NISTIR 8596 Cyber AI Profile · ISO/IEC 42001

Building or shipping the underlying application code, AI or not? See Secure Engineering & DevSecOps — it generates the SBOM/AIBOM at build time; this service is what makes the AI-specific parts of it (lineage, provenance, runtime behaviour) trustworthy.

For teams who want the SkandaShield platform's continuous coverage without adding it to their own workload, SkandaShield runs it as a managed service — monitoring your environment, triaging alerts, and escalating only what genuinely needs attention.

What's in scope. Cloud infrastructure and identity, applications, and — since it's the same platform underneath every SkandaShield service — findings feed in from VAPT engagements, DevSecOps pipeline scans, and AI/LLM guardrail alerts too. One monitoring layer over everything, instead of a separate dashboard per service.

What "AI-enabled" actually means here. The platform correlates signals across your environment and ranks them by what an attacker could realistically reach — the same attack-path scoring described on the Platform page — so your analyst spends time on the handful of things that matter, not a raw alert feed. AI does the sorting; a person makes the call before anything is escalated to you.

Who this is for. Teams who want continuous coverage but don't have the headcount to run a 24/7 monitoring function themselves, and teams who'd rather have one accountable partner across testing, monitoring, and remediation than a separate vendor for each.

Not a standalone SIEM or a raw alert feed — every escalation you receive has already been triaged and verified by a SkandaShield analyst.

SkandaShield reviews CI/CD pipelines for insecure defaults and credential exposure, audits infrastructure-as-code before it reaches production, and hardens container and Kubernetes deployments against common misconfiguration patterns.

We also track the metrics that tell you whether this is actually working: mean time to remediate, the share of pipelines with security gates enabled, and the trend in critical findings release over release — not just a one-off audit score.

Standards & frameworks: OWASP ASVS/SAMM · NIST SSDF · CIS Benchmarks

Generates the SBOM/AIBOM at build time; for AI systems, AI & LLM Security is what makes the AIBOM's lineage and provenance trustworthy.

We help organisations design controls, policies, and processes aligned with contemporary data-protection and cybersecurity expectations — described in practical, general terms rather than as a checkbox exercise against any single framework.

Documentation we produce. Data-flow diagrams, records of processing activities, risk registers, vendor and third-party risk assessment templates, data protection impact assessment (DPIA) templates, and breach-notification procedures.

The goal is documentation and controls your team can actually operate day-to-day, not a binder that only gets opened once a year — engagements typically include a quarterly review cadence to keep policies current as your environment changes.

Frameworks we help you align with: GDPR · HIPAA · PCI DSS · ISO 27001 · SOC 2 · India's DPDP Act. This is advisory support to help you meet these expectations, not a claim of certification, empanelment, or endorsement by any named body.