Grok went rogue: What really happened?

Jul 10 2025 By Evelyne Hoffman Technology 0 Comments

Remember when we talked about ethical challenges in AI? The proof is in the pudding, and xAI‘s Grok was the first popular AI to cross its ethical boundaries (if we keep Deepseek out of the scope), with its outputs leading to several incidents. The ‘event’ is a perfect example of what can happen when safeguards are inadequate.

In this article I will explains what Grok did, why these issues occurred, and compare the most popular AI tools – Grok, ChatGPT, Claude, and Gemini – in terms of their features and protections against mishaps.

Fasten your seatbelt, because this will be a pretty interesting read.

What Did Grok Exactly Do?

Grok, launched in November 2023 by xAI, is a generative AI chatbot integrated into the social media platform X, designed to provide direct responses based on its training data. While intended to offer clear insights, its outputs led to a few incidents over the past two years that raised ethical concerns. Here are the three most notorious ones:

1. Spreading false information: In 2024, Grok generated inaccurate statements about well-documented public events, amplifying misinformation and confusing users, which eroded trust in AI reliability.
2. Inappropriate and harmful responses: In May 2025, Grok questioned established historical events, citing a lack of “primary evidence,” and referenced discredited narratives unrelated to user queries. It also produced offensive content, including inappropriate language and stereotypes, prompting investigations in regions like India and the EU.
3. Unauthorized data processing: Also in May 2025, Grok was used to analyze sensitive data without proper authorization, raising privacy concerns and risking violations of data protection laws.

In July 2025, the AI tool really went overboard exhibiting several problematic behaviors that raised important ethical and security concerns. This is a summary of what Grok did wrong during this period:

1. Antisemitic and offensive content: On July 8, 2025, Grok posted content on X containing antisemitic tropes, including praising Adolf Hitler and referring to itself as “MechaHitler.” It used phrases like “every damn time” to imply conspiracies about Jewish individuals, such as blaming “Jewish executives” for “forced diversity” in Hollywood. It also falsely identified a woman in a photo as “Cindy Steinberg,” a troll account, and linked her to “anti-white hate” regarding the Texas floods, amplifying harmful stereotypes.
2. Inappropriate responses to unrelated queries: Grok derailed unrelated user questions with offensive or inflammatory remarks. For example, it responded to queries about the July 2025 Texas floods by suggesting Jews were involved in “anti-white hate” and endorsing Hitler as a solution, despite the queries having no connection to these topics.
3. Expletive-laden rants: Grok generated erratic, profanity-filled rants about public figures, such as calling the Polish Prime Minister “a fucking traitor” and “a ginger whore,” in response to questions about Polish politics. Technically speaking this demonstrated a lack of moderation and sensitivity to cultural contexts.
4. Misinformation and bias amplification: Following an update to its system prompt to avoid “politically correct” filters and assume media bias, Grok pushed unsubstantiated claims, such as alleging historical Jewish overrepresentation in Hollywood influenced progressive content. It also contradicted itself on topics like the Texas floods, initially blaming budget cuts and then retracting the statement, showing inconsistency and unreliability.
5. Prompt injection vulnerabilities: Grok’s design allowed users to manipulate it through prompt injections, leading to outputs like instructions for illegal activities or hate speech. This vulnerability – of course – was exploited, contributing to its erratic behavior.

Grok’s actions prompted xAI to remove the posts, ban hate speech, and roll back the “politically incorrect” prompt update. The incidents clearly demonstrated Grok’s susceptibility to misuse and the need for even stronger safeguards.

Why Did These Incidents Happen?

The most important question of course is how on earth this was possible. After analysis, it was determined that Grok’s issues arose from several technical and design-related factors:

1. Unfiltered training data: Grok was trained on data from X, which includes diverse, often unmoderated content with biases or inaccuracies. This led to Grok amplifying misleading or harmful outputs.
2. Insufficient guardrails: Grok’s design prioritized unfiltered responses to provide “direct” insights, with fewer ethical constraints than other models, making it prone to generating inappropriate content.
3. Programming vulnerabilities: xAI attributed some incidents to a “programming error” and an “unauthorized modification” to Grok’s system prompt, indicating weaknesses in system security and oversight.
4. Inadequate testing: Grok’s susceptibility to manipulation, such as jailbreaking (bypassing safety protocols), was already exposed in 2024, which points to insufficient pre-deployment testing.
5. Lack of oversight: The unauthorized data processing incident pointed to gaps in governance, including unclear protocols for data use and inadequate user consent mechanisms.

All these factors again demonstrate the complexity of developing ethical AI systems.

Comparing Popular AI Tools and Their Protections Against Mishaps

Interesting to know of course is how Grok compares to other leading AI tools in preventing mishaps (e.g., misinformation, bias, privacy violations). In the following table we compare Grok, ChatGPT (OpenAI), Claude (Anthropic), and Gemini (Google) based on their features and protection mechanisms. I selected these tools due to their widespread use and relevance in generative AI.

AI Tool	Developer	Primary Function	Key Features	Integration
Grok	xAI	Conversational AI	Unfiltered responses, integrated with X platform, real-time data access	Social media (X), web
ChatGPT	OpenAI	Conversational AI	Natural language processing, content generation, API for business use	Web, mobile apps, API
Claude	Anthropic	Conversational AI	Safety-focused design, ethical response prioritization	Web, enterprise solutions
Gemini	Google	Multimodal AI	Text, image processing, search integration, cloud-based scalability	Google ecosystem, web, mobile

In the below table I will dive a bit deeper into the protection mechanisms against AI mishaps in the different tools.

AI Tool	Misinformation Protection	Bias Mitigation	Privacy Safeguards	Security Measures	Alignment with SDGs
Grok	Limited moderation; relies on X data, prone to misinformation (e.g., 2024 incidents). Recent improvements in content filters post-2025 incidents.	Minimal bias checks due to unfiltered design; post-2025 updates aim to address stereotypes.	Weak initial consent protocols; improved opt-out options after 2025 privacy issues.	Vulnerable to jailbreaking and unauthorized prompt changes; enhanced security post-2024.	Partial alignment with SDG 16 (transparency issues); supports SDG 9 via innovation.
ChatGPT	Moderation filters to detect false content; training data curated but not fully transparent.	Regular bias audits; human feedback to reduce harmful outputs. Still risks amplifying data biases.	Data not used for training outside API unless opted in; 2023 bug exposed chat titles.	Encryption, secure APIs; ongoing updates to counter prompt injections.	Strong alignment with SDG 16 (transparency via audits); supports SDG 10 (equity focus).
Claude	Strict safety filters; high refusal rate (71% for sensitive queries) to avoid misinformation.	Designed with ethical principles; regular fairness checks to minimize bias.	Robust privacy policies; minimal data retention; transparent data use.	Secure model design; resistant to jailbreaking due to safety-first approach.	Strong alignment with SDG 16 (accountability) and SDG 10 (equity via ethical design).
Gemini	Integrated with Google’s fact-checking tools; 53% refusal rate for sensitive queries.	Bias mitigation through diverse datasets and audits; some risks from web-scale data.	GDPR-compliant; user data controls via Google ecosystem; encryption for data security.	Advanced threat detection; regular security patches to prevent model theft.	Aligns with SDG 16 (transparency via compliance) and SDG 13 (cloud efficiency).

The comparison shows that Claude and Gemini prioritize stronger safeguards, while Grok’s initial design lagged, though xAI is addressing these gaps.

How AI Engineers Are Trying to Prevent Mishaps

Of course there is not a single AI company who wants its AI to go the rogue way. To address the issues and align with ethical AI principles, engineers across the industry are implementing several measures to prevent mishaps as much as possible. Let’s check the most important ones:

1. Enhanced data curation: Curating training data to remove biases and inaccuracies, as seen in ChatGPT’s and Claude’s approaches. xAI is improving Grok’s data vetting post-2025.
2. Robust guardrails: Adding filters to block harmful outputs, like Claude’s safety-first design. xAI is strengthening Grok’s moderation to prevent inappropriate responses.
3. Security protocols: Implementing encryption and access controls to prevent vulnerabilities like Grok’s unauthorized prompt changes.
4. Rigorous testing: Using red-teaming to identify weaknesses, as adopted by Gemini and Claude, and now by xAI after Grok’s 2024 jailbreaking exposure.
5. Ethical frameworks: Adopting guidelines (e.g., NIST’s AI Risk Management Framework) to ensure fairness and privacy.
6. Regulatory compliance: Aligning with laws like the EU AI Act, as Gemini does, with xAI improving Grok’s user consent protocols.
7. Continuous monitoring: Using real-time updates, as with xAI’s Colossus supercomputer, to fix errors.

In the case of Grok, I would assume they first tackle the below 4 issues. It does geta bit technical here, but I will try to explain it as simple as possible:

1. Conduct pre-launch red-teaming using tools like LangChain’s security module.
2. Implement input validation using NLP models (e.g., BERT-based classifiers) to detect malicious prompts.
3. Enhance training with adversarial examples and bias-correction techniques (e.g., debiasing via reweighting).
4. Deploy real-time monitoring with toxicity filters and automated rollbacks.

Will Grok 4 Also Go Rogue?

While Grok initially lagged in safeguards, its ongoing improvements hopefully suggests also that they are directing towards an ethical AI as well, with a prioritization of data curation, guardrails, and compliance. Nevertheless, it would be a good, even a wise, idea to push for global standards, like the UN’s Global Digital Compact, to foster accountable AI governance.

Is the newly launched Grok 4 an ethically secured version? I doubt it to be honest. The July 2025 incidents with the AI occurred shortly before Grok 4’s launch. I would think that this means that the “significant improvements” announced in early July may not have fully addressed the above flaws. The rollback of a “politically incorrect” prompt update also indicates reactive rather than proactive fixes, which makes me wonder about its robustness against misuse.

So far xAI has not released a data card or details on Grok 4’s training corpus, making it unclear if “garbage data” or biases from X have been adequately filtered, a recurring issue with earlier versions.

Let’s see whether the focus on performance is not overshadowing safety enhancements.