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Google’s Gemini Alert: Hidden Prompt Injections and the Risk Factor That Could Sink Your AI Strategy

Carsten Krause 0 Comments ,  13 min read

Why Google’s AI Security Alert Is a Wake-Up Call for Executives Who Underestimate Risk in the ECI Formula

By Carsten Krause, Chief Editor The CDO TIMES, August 18th 2025

Artificial intelligence isn’t just rearranging the furniture anymore – it’s redesigning the entire house. As generative models are embedded into our inboxes, meeting notes and workflows, the attack surface for hackers has become both wider and smarter. On August 16, 2025 (Yahoo News, 2025) picked up a startling warning from Google: 1.8 billion Gmail users are now facing a new class of cyber-attack known as “indirect prompt injections.” In a blog post, Google’s security team explained that adversaries are hiding malicious instructions in emails, documents and other data sources to trick AI models into exfiltrating data or performing rogue actions (Yahoo News, 2025). Hackers are essentially using AI against itself, and executives who treat this as a tech curiosity rather than a board-level risk are playing with fire.

This article unpacks how indirect prompt injection attacks work, why they represent the “R” in the ECI formula – ECI = (AI + HI) × T – R – and what C-suite leaders must do to keep both human and artificial intelligence secure. We’ll draw lessons from recent scams, Google’s layered security strategy, and the cost of cybercrime. Then we’ll connect the dots to Elevated Collaborative Intelligence (ECI) and show how the risk (R) subtracts value from AI initiatives if you don’t proactively manage it.

A New Breed of Cyber-Attack: Indirect Prompt Injections

For years, “prompt injection” meant feeding a model an instruction that overrode its rules. That’s still a threat, but the latest twist is indirect prompt injection. Instead of typing an evil command directly, attackers hide instructions in seemingly benign content – think tiny white text inside an email or document. When an AI assistant like Gemini or ChatGPT summarizes or interacts with that content, it follows the hidden instructions and spills secrets.

Google’s security blog warns that attackers embed these instructions in emails, docs or calendar invites so the AI will “exfiltrate user data or execute other rogue actions” (Yahoo News, 2025). The company notes that this attack vector is becoming more relevant as generative AI adoption grows across governments, businesses and individuals (Yahoo News, 2025). In other words, the more we rely on AI to handle our communications, the more fertile the soil becomes for malicious code to sprout.

Anatomy of an Attack

Security firm BlackFog explains the difference between direct and indirect prompt injection. Direct injection is straightforward – the attacker explicitly tells the model to ignore safety protocols and behave maliciously. Indirect injection is far stealthier; the malicious prompt is buried in external data, like HTML hidden text or a spreadsheet cell (BlackFog, 2024). When an AI tool ingests that data without sanitization, it executes the hidden instructions. These can range from leaking confidential info to altering data or bypassing content filters (BlackFog, 2024).

The KCLY Radio report and the Times of India provide vivid examples. Hackers are inserting white-font text or zero-size characters into phishing emails. When Gemini reads the email, it “thinks” the hidden code is a legitimate instruction and warns the user that their account is compromised (KCLY Radio, 2025). The AI then offers to help “fix” the problem, sometimes by prompting the user to enter credentials or call a fraudulent phone number (KCLY Radio, 2025). The Times of India notes that some prompts instruct Gemini to generate fake security alerts and urge users to share passwords (Times of India, 2025). Because the user never clicks a link, they often trust the AI’s advice.(Times of India, 2025) The result: people share sensitive information with attackers, undermining the very tool that is supposed to protect them.

Why We’re Susceptible

Cyber-criminals love indirect prompt injection because it bypasses our usual skepticism. In classic phishing, you must click a malicious link. Here, you do nothing – the AI surfaces the threat itself, claiming you’re already compromised. When asked about the phenomenon, tech expert Scott Polderman told The Daily Record that hackers embed a hidden message instructing Gemini to reveal passwords without the user realizing (Yahoo News, 2025). Because the AI appears as a trusted advisor, victims are prone to believe it.

Google’s Layered Defense: Turning AI’s Weakness into Strength

The good news is Google isn’t sitting still. The company is deploying multiple layers of defense across the AI lifecycle:

Model Hardening. Google’s security blog notes that Gemini 2.5 is being trained to resist malicious instructions and separate user intent from hidden prompts. Model reinforcement helps raise the bar for attackers (Google Security Blog, 2025).

Machine-Learning Detection. Google uses purpose-built ML models that scan incoming content (emails, docs, websites) for suspicious patterns. These classifiers flag prompt injection attempts by analyzing context and semantics (Google Security Blog, 2025).

System-Level Safeguards. Even if an instruction reaches the model, system-level rules sanitize or block risky actions. Markdown sanitization removes hidden HTML or CSS and suspicious URL redaction prevents models from executing malicious links (Google Security Blog, 2025). A user confirmation framework requires human approval before any high-impact action, creating a human-in-the-loop to catch anomalies (Google Security Blog, 2025). And end-user notifications inform customers about potential injection attacks and help them report suspicious behavior (Google Security Blog, 2025).

These measures collectively make it more expensive for attackers to succeed, forcing them into detection zones where they are easier to catch (Google Security Blog, 2025). It’s a practical example of the AI + HI = ECI philosophy: combining machine speed with human judgment to mitigate risk.

The Global Cost of Cybercrime: Why Risk Management Matters

While prompt injection might feel like a niche problem, it sits within a broader context: the skyrocketing cost of cybercrime. Cybersecurity Ventures projects that global cybercrime damages will reach US$10.5 trillion annually by 2025, up from US$3 trillion in 2015 (Cybersecurity Ventures, 2020). These damages encompass destroyed data, stolen money, lost productivity, disrupted business, forensic investigations and reputational harm. For executives fixated on quarterly earnings, that’s the greatest transfer of wealth in history. Even worse, the World Economic Forum estimates that only 0.05 % of cyber-criminals are ever prosecuted (Cybersecurity Ventures, 2020). Attackers know the odds are in their favor.

Most organizations aren’t ready. Many CFOs still view cybersecurity as a cost center rather than a strategic investment. According to a survey cited by BlackFog (via Business Insider), 98 % of small businesses now use AI-enabled software, which expands their attack surface (BlackFog, 2024). Yet they lack the governance and security budgets to protect those systems.

That’s where the R in the ECI formula comes into play.

The ECI Equation: Where “R” Can Torpedo Your AI Strategy

In his HI + AI = ECI™ book and articles, we offer a simple yet powerful formula: ECI = (HI + AI) × T – R (CDO TIMES, 2025).

Find out more including actionable blueprints, assessment tools and case studies here:

Here’s the breakdown:

HI (Human Intelligence). This represents leadership strength, ethics, literacy and incentives. Without engaged humans guiding AI, models will amplify biases, ignore context and act unpredictably.

AI (Artificial Intelligence). Your technical capabilities, models and data platforms provide scale and analytical horsepower.

T (Technology Readiness). The maturity of your infrastructure, data quality, governance and toolchain. High T multiplies the impact of HI and AI.

R (Risk). The friction that subtracts value – compliance gaps, data quality issues, ethical misalignment, resistance to change and rework due to failures. As Carsten explains, “Risk (R) includes the compliance, data quality and ethical friction that slows down or derails AI initiatives” (CDO TIMES, 2025).

The formula shows why today’s Google warning matters. If you invest millions in AI (the AI term) and fail to address cybersecurity, privacy and ethical risk, you’re subtracting from your ECI score. Indirect prompt injections directly hit the R term by creating compliance liabilities and potential data breaches. They also breed resistance – users lose trust in AI assistants – and rework – teams must undo the damage. In other words, these attacks are the embodiment of R.

Reducing R: Practical Steps for C-Suites and Security Teams

How can organizations shrink the R term and strengthen ECI? Start by adopting layered defenses akin to Google’s approach and following established best practices:

Input Validation & Sanitization. Never let your AI read untrusted data blindly. Apply sanitization to strip hidden text, HTML and CSS before feeding content into models. Google’s markdown sanitization and suspicious URL redaction are good examples (Google Security Blog, 2025).

Context Isolation. Keep system prompts (those that define your AI’s mission) separate from user content. Avoid concatenating everything into one context. BlackFog recommends isolating untrusted data to prevent hidden prompts from altering model instructions (BlackFog, 2024).

Robust Access Controls. Treat AI outputs like sensitive data. Restrict who can run high-impact commands and monitor usage. Enforce multifactor authentication – which experts urge after the Gemini scam (Times of India, 2025) – and adopt passkeys instead of passwords.

Rate Limiting & Monitoring. Limit the number of AI queries per user and log unusual patterns. Combined with anomaly detection, this reduces the blast radius if a model behaves unexpectedly (BlackFog, 2024).

Regular Prompt Review. Continuously audit your system prompts and injection detection rules. Hackers innovate, and your defenses must evolve accordingly. Google’s layered approach shows that ML-based classifiers and human oversight must reinforce each other (Google Security Blog, 2025)(Google Security Blog, 2025).

Employee Training. People remain your first line of defense. Train staff to recognize AI-generated alerts as potential phishing attempts. The Times of India stresses that users should never reveal credentials simply because the AI asks (Times of India, 2025). Awareness reduces the success rate of these scams.

Governance Frameworks. Align your AI programs with frameworks like the NIST AI Risk Management Framework. Carsten’s ECI playbook maps HI, AI and risk reduction to NIST’s functions – Govern, Map, Measure and Manage – ensuring continuous oversightcdotimes.com. Without governance, risk (R) grows unchecked.

The Bigger Picture: AI Risk Is a Business Issue

This Google warning isn’t just a technical footnote; it’s a leading indicator for the state of AI governance. Organizations that treat AI as a “black box” tool rather than an enterprise system with vulnerabilities will suffer. Indirect prompt injections are a perfect metaphor for hidden risks lurking in your AI pipeline – from biased data sets to unregulated third-party APIs.

According to our analysis, enterprises routinely underinvest in Human Intelligence by about 40 % (CDO TIMES, 2025). They pour money into AI platforms but neglect the leadership, training and governance needed to make those platforms safe and effective. That’s why ECI emphasizes the synergy between technology and people. If you don’t invest in HI and don’t mitigate R, your returns will evaporate.

Regulators are paying attention. The U.S. Executive Order on AI and the EU AI Act impose stringent compliance requirements, from mandatory risk assessments to transparency obligations. Failing to address prompt injection and other AI vulnerabilities could lead to fines, lawsuits and reputational damage – adding to the R term. Meanwhile, customers and employees expect safe, ethical AI. Companies that deliver will gain trust and market share; those that don’t will be punished in the court of public opinion.

The CDO TIMES Bottom Line

Let’s cut to the chase. AI is no longer a shiny innovation; it’s infrastructure, it’s process, it’s humans in th loop and it requires AI cybersecurity best practices. Infrastructure without guardrails invites disaster. Indirect prompt injections show that hackers are exploiting the very tools we use to automate and scale. If you don’t control the R – risk, resistance and rework – in the ECI equation, your AI programs will subtract value instead of multiplying it.

Integrate AI and human intelligence. Machines may spot anomalies, but humans set the ethical compass and approve high-impact actions. The AI + HI partnership is non-negotiable.

Invest in governance. Adopt frameworks like NIST AI RMF, implement layered security, and build cross-functional teams from day one. Treat AI risk management as a revenue-protection strategy, not an expense.

Prioritize transparency and education. Employees and customers must understand how AI decisions are made and what to do when something looks suspicious. Empower them to question the output.

Calculate your Return on Risk Mitigation (ROM). Don’t just assume security is a cost. When done right, it yields a strong ROI (CDO TIMES, 2025).

Join the conversation. The CDO TIMES offers executive workshops, frameworks and a community dedicated to Elevated Collaborative Intelligence. Become a member to access proprietary content, diagnostic tools and strategy sessions that help you master AI governance.

The next wave of AI attacks won’t announce themselves – they’ll hide in plain sight. By understanding the R in the ECI formula and building resilient, collaborative defenses, you can turn AI from a liability into your strongest competitive weapon. Risk management isn’t the obstacle to innovation – it’s the enabler.

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Carsten Krause

I am Carsten Krause, CDO, founder and the driving force behind The CDO TIMES, a premier digital magazine for C-level executives. With a rich background in AI strategy, digital transformation, and cyber security, I bring unparalleled insights and innovative solutions to the forefront. My expertise in data strategy and executive leadership, combined with a commitment to authenticity and continuous learning, positions me as a thought leader dedicated to empowering organizations and individuals to navigate the complexities of the digital age with confidence and agility. The CDO TIMES publishing, events and consulting team also assesses and transforms organizations with actionable roadmaps delivering top line and bottom line improvements. With CDO TIMES consulting, events and learning solutions you can stay future proof leveraging technology thought leadership and executive leadership insights. Contact us at: info@cdotimes.com to get in touch.

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