What is AISymmetric Aegis?

AISymmetric Aegis is the AI-augmented, ethical (white-hat) security arm of AISymmetric, an AI boutique consulting firm. Aegis delivers passive, authorized security assessments across the platforms businesses actually run on — Salesforce, AWS, Azure, GCP, LLM/AI systems, and compliance frameworks like SOC 2 and ISO 27001. Every assessment is read-only by default, non-destructive, and reviewed by a senior human practitioner.

How is AISymmetric Aegis different from a traditional penetration testing firm?

Three ways. First, coverage: traditional pen-test firms focus on the network perimeter, while Aegis assesses every layer a business runs on — Salesforce, cloud (AWS/Azure/GCP), LLM/AI systems, and compliance. Second, method: Aegis is AI-augmented and human-verified, so it covers more surface faster without dumping raw scanner output. Third, ethics: assessments are passive and read-only by default, and Aegis leads with a free findings-first Quick Scan rather than a sales call.

Is an Aegis security assessment safe to run on production systems?

Yes. Every Aegis assessment is passive and read-only by default, explicitly authorized in writing, and non-destructive. We assess configurations, permissions, and exposure — we do not exploit vulnerabilities or disrupt live systems. The goal is zero production impact, so assessments are safe to run against the environments you depend on.

Which platforms and systems does Aegis assess?

Aegis covers six surfaces: Salesforce (orgs, profiles, permissions, data exposure), AWS, Azure, and GCP (identity, storage exposure, misconfiguration), LLM/AI systems (prompt injection, data leakage, agent permissions), and compliance readiness (SOC 2, ISO 27001). This full-stack coverage reflects how modern businesses actually operate, rather than the network-only scope of legacy testing.

What is LLM (AI) security and why does it matter?

LLM security is the practice of protecting large-language-model and AI-agent systems from risks that traditional application security misses — prompt injection, sensitive-data leakage, jailbreaks, and over-permissioned agents that can take real actions. As companies deploy AI into customer-facing and internal workflows, these become live attack surfaces. Aegis tests for them and provides a governance framework to deploy AI safely.

Is the Aegis Quick Scan really free, and what does it show?

Yes, the Aegis Quick Scan is genuinely free, requires no login, and runs in under a minute. It's a passive, externally visible snapshot of a website's security posture — security headers, TLS configuration, exposure signals — giving you an immediate, honest read before any paid engagement or sales conversation.

How much does a full security assessment cost?

Pricing depends on scope — how many platforms are in play and the depth of review. Because Aegis starts every relationship with a free Quick Scan and a findings-first conversation, you see real value before committing. Contact AISymmetric Aegis for a scoped quote based on your specific environment.

How does Aegis help with SOC 2 and ISO 27001 compliance?

Aegis runs a gap assessment against SOC 2 or ISO 27001 controls, maps your existing policies and technical controls to the framework, identifies what's missing, and provides a remediation and evidence-tracking plan. Fractional CISO (vCISO) advisory is available to help turn assessment findings into an auditable, defensible security posture over time.

Who is behind AISymmetric Aegis?

AISymmetric Aegis is operated by AISymmetric, founded by Tyler Perleberg. AISymmetric is an AI boutique consulting firm that architects and builds enterprise AI systems — which is precisely why its security arm can secure AI the way it is actually built and deployed. The same practitioners who design AI solutions review the security of AI and cloud platforms under the Aegis brand.

How do I get started with AISymmetric Aegis?

Start with the free Aegis Quick Scan for an immediate passive snapshot, then request a scoped assessment. From there, Aegis agrees on scope, obtains written authorization, runs an AI-augmented and human-verified assessment across your platforms, and delivers a prioritized findings report with a remediation roadmap.

5 min read·Updated July 16, 2026

What is LLM security (and what is prompt injection)?

Q: What is the "AI asymmetry" in cybersecurity?

The AI asymmetry is the widening gap between AI-armed attackers and human-speed defenders. Adversaries now use large language models to discover flaws, write exploits, and scale attacks faster than traditional security teams can review them. AISymmetric Aegis closes that gap by putting the same AI leverage on the defender's side — AI-augmented, human-verified assessments that match the speed of modern threats.

LLM security protects large-language-model and AI-agent systems from risks traditional application security misses — prompt injection, data leakage, jailbreaks, and over-permissioned agents.

Definition

LLM security is the practice of protecting systems built on large language models — chatbots, copilots, retrieval-augmented apps, and autonomous agents — from misuse and compromise. It addresses failure modes that classic application security was never designed for, because the model itself interprets untrusted natural-language input as instructions.

Prompt injection

Prompt injection is the top LLM-specific risk. An attacker plants instructions in content the model will read — a web page, a document, an email, a support ticket — that override the developer's intended behavior. Indirect prompt injection is especially dangerous for agents that browse or ingest external data, because the malicious instruction arrives inside otherwise-normal content.

Testing for prompt injection means probing whether untrusted input can change the system's behavior, exfiltrate hidden context, or trigger tools it shouldn't.

Data leakage and jailbreaks

Data leakage happens when a model reveals sensitive context — system prompts, other users' data, secrets, or PII — through crafted queries. Jailbreaks bypass safety and policy constraints to make the model produce prohibited output or take prohibited actions. Both are assessed by adversarially prompting the system and inspecting what it discloses or does.

Over-permissioned agents

The highest-impact LLM risk is an agent with real permissions — the ability to send email, move money, modify records, or call internal APIs — combined with a prompt-injection weakness. The mitigation is least privilege: scope every tool and credential tightly, require confirmation for irreversible actions, and log everything. An assessment reviews exactly which actions an agent can take and whether untrusted input can trigger them.

Governance

Beyond testing, LLM security needs governance: an acceptable-use policy, data-handling rules for what may enter prompts, human-in-the-loop checkpoints for consequential actions, and monitoring. AISymmetric Aegis pairs prompt-injection, data-leakage, and agent-permission testing with a practical governance framework so AI can be deployed safely.

Frequently asked

What is the difference between prompt injection and jailbreaking?

Jailbreaking bypasses a model's safety rules to produce prohibited output. Prompt injection overrides the application's intended instructions using untrusted input — often hidden inside content the model reads — and is especially dangerous for agents with tool access.

Can traditional application security tools catch LLM vulnerabilities?

Largely no. Traditional tools look for code-level flaws; LLM risks arise from the model interpreting natural language as instructions. Assessing them requires adversarial prompting and a review of agent permissions and data flows.

How do you test an AI agent for security issues?

By enumerating every tool and permission the agent holds, then attempting indirect prompt injection through the data it ingests to see whether untrusted input can trigger sensitive actions or leak context — all under explicit authorization.

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