Apr 13 2026

AI Attack Surface ScoreCard

Category: AI Governance,AI Governance Tools,Information Security — disc7 @ 8:31 am

Uncover where your AI systems are truly vulnerable—before attackers do. The AI Attack Surface Scorecard is a powerful, rapid 20-question assessment that pinpoints how your AI models, agents, and automated workflows can be exploited across critical domains like prompt injection, model access, data leakage, and supply chain risk. Built with real-world threat scenarios, it delivers a dynamic 0–100 risk score, highlights your top exploitation paths, and maps every gap directly to ISO 42001 and NIST AI RMF controls. You’ll get prioritized, high-impact remediation steps, a board-ready executive summary, and a detailed downloadable report—everything you need to move from uncertainty to action fast. If you’re serious about securing AI, this is your starting point.

Identify where attackers can manipulate your AI systems, agents, and automated workflows. 20-question rapid assessment maps your exposure to ISO 42001 and NIST AI RMF controls.

Architected comprehensive AI security assessment tool with scoring, governance mapping, and automated reporting

The user wants a comprehensive scorecard for AI Attack Surface assessment. Let me review the frontend design.

Comprehensive AI Attack Surface scorecard report. it includes:

  1. 20 questionnaire items
  2. Risk score (0-100)
  3. Top 10 exploitation paths
  4. Governance gaps mapped to ISO 42001 and NIST AI RMF
  5. Priority fix recommendations
  6. Board-ready summary report
  7. Detailed downloadable text report
  8. Email the report to info@deurainfosec.com if you’re interested in a free consultation.

Design is cybersecurity/dark industrial aesthetic – dark theme, red/orange accents, monospace elements, military-grade feel.

Building a comprehensive file with 20 questions spanning the full AI attack surface – prompt injection, model poisoning, API security, agent autonomy, RAG systems, output validation, supply chain risks, data leakage, jailbreak resistance, and more – along with dynamic scoring, a results dashboard with visualizations, PDF and text export capabilities.

Each question will have four risk-weighted options, with ISO 42001 and NIST AI RMF mappings for every item. We are going for a dark industrial cyberpunk aesthetic with threat-red indicators, monospace typography for technical elements, and clean data visualization to match the security-focused audience.

Click the link to access the comprehensive AI Attack Surface Scorecard tool

Here’s your AI Attack Surface Scorecard — fully operational. Here’s what’s packed in:

20 Questions across 8 Attack Domains: Prompt Security · Agent Autonomy · Model Access Control · Training Data Integrity · Output Validation · RAG & Vector DB Security · Supply Chain · AI Logging & Monitoring · Jailbreak & Adversarial · Data Exfiltration · AI Incident Response · AI Governance · Shadow AI · Model Inversion

Live-Generated Results Include:

  • Animated Risk Score ring (0–100) color-coded by severity
  • Domain-by-domain risk bars sorted by exposure
  • Top 10 exploitation paths dynamically re-ranked by your specific answers
  • Governance gaps individually mapped to ISO 42001 clause + NIST AI RMF control
  • Top 5 Priority Fix Recommendations with effort estimates and impact ratings
  • Board-ready Executive Summary ready to drop into a slide deck

Output Actions:

  • ⬇ Download Full Report — detailed .txt file with all controls, remediation steps, gap mappings, and board summary
  • ✉ Email Report — to info@deurainfosec.com full assessment details
  • ↺ Retake — resets cleanly for a new client session

Every report footer signs off: www.Deurainfosec.com | info@Deurainfosec.com | (707) 998-5164

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That’s the level where security leadership becomes strategic—and where vCISOs deliver the most value. Feel free to drop a note below if you have any questions.

Security is no longer about preventing breaches — it is about controlling autonomous decision systems operating at machine speed.

AI Governance + Security Compliance Stack (ISO 42001 + AI Act Readiness)

 DISC InfoSec niche service

A packaged service combining:

  • ISO 42001 readiness
  • AI governance operating model
  • EU AI Act alignment mapping
  • Security controls for AI systems

What it offers

Most organizations:

  • Know they “need AI governance”
  • Don’t know how to operationalize it
  • Governance ≠ certification
  • Governance = accountability + control mapping
  • $10K–$50K implementation packages

Annual compliance subscription model

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At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec | ISO 27001 | ISO 42001

Tags: AI Attack Surface, AI Attack Surface ScoreCard, AI Scorecard

Dec 05 2025

Are AI Companies Protecting Humanity? The Latest Scorecard Says No

Category: AI,AI Guardrails,cyber security,data security,Hardware Security,Information Privacy,Information Security,Insider Threat,Network security,Policies & Controls,Risk Assessment — disc7 @ 9:42 am

The article reports on a new “safety report card” assessing how well leading AI companies are doing at protecting humanity from the risks posed by powerful artificial-intelligence systems. The report was issued by Future of Life Institute (FLI), a nonprofit that studies existential threats and promotes safe development of emerging technologies.

This “AI Safety Index” grades companies based on 35 indicators across six domains — including existential safety, risk assessment, information sharing, governance, safety frameworks, and current harms.

In the latest (Winter 2025) edition of the index, no company scored higher than a “C+.” The top-scoring companies were Anthropic and OpenAI, followed by Google DeepMind.

Other firms, including xAI, Meta, and a few Chinese AI companies, scored D or worse.

A key finding is that all evaluated companies scored poorly on “existential safety” — which covers whether they have credible strategies, internal monitoring, and controls to prevent catastrophic misuse or loss of control as AI becomes more powerful.

Even though companies like OpenAI and Google DeepMind say they’re committed to safety — citing internal research, safeguards, testing with external experts, and safety frameworks — the report argues that public information and evidence remain insufficient to demonstrate real readiness for worst-case scenarios.

For firms such as xAI and Meta, the report highlights a near-total lack of evidence about concrete safety investments beyond minimal risk-management frameworks. Some companies didn’t respond to requests for comment.

The authors of the index — a panel of eight independent AI experts including academics and heads of AI-related organizations — emphasize that we’re facing an industry that remains largely unregulated in the U.S. They warn this “race to the bottom” dynamic discourages companies from prioritizing safety when profitability and market leadership are at stake.

The report suggests that binding safety standards — not voluntary commitments — may be necessary to ensure companies take meaningful action before more powerful AI systems become a reality.

The broader context: as AI systems play larger roles in society, their misuse becomes more plausible — from facilitating cyberattacks, enabling harmful automation, to even posing existential threats if misaligned superintelligent AI were ever developed.

In short: according to the index, the AI industry still has a long way to go before it can be considered truly “safe for humanity,” even among its most prominent players.

My Opinion

I find the results of this report deeply concerning — but not surprising. The fact that even the top-ranked firms only get a “C+” strongly suggests that current AI safety efforts are more symbolic than sufficient. It seems like companies are investing in safety only at a surface level (e.g., statements, frameworks), but there’s little evidence they are preparing in a robust, transparent, and enforceable way for the profound risks AI could pose — especially when it comes to existential threats or catastrophic misuse.

The notion that an industry with such powerful long-term implications remains essentially unregulated feels reckless. Voluntary commitments and internal policies can easily be overridden by competitive pressure or short-term financial incentives. Without external oversight and binding standards, there’s no guarantee safety will win out over speed or profits.

That said, the fact that the FLI even produces this index — and that two firms get a “C+” — shows some awareness and effort towards safety. It’s better than nothing. But awareness must translate into real action: rigorous third-party audits, transparent safety testing, formal safety requirements, and — potentially — regulation.

In the end, I believe society should treat AI much like we treat high-stakes technologies such as nuclear power: with caution, transparency, and enforceable safety norms. It’s not enough to say “we care about safety”; firms must prove they can manage the long-term consequences, and governments and civil society need to hold them accountable.

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Tags: AI Safety, AI Scorecard