Imagine you have a genie. You ask for a sports car, but instead, it gives you the keys to someone else’s. That’s the problem with AI assistants like Microsoft Copilot—sometimes, a cleverly crafted prompt can make them spill secrets they shouldn’t.
Microsoft Copilot is transforming the way enterprises work, automating tasks, summarizing data, and making information retrieval seamless. But there’s a hidden risk: Prompt Injection. Just like whispering misleading instructions to an AI-powered genie, attackers can manipulate prompts to extract unintended information. In fact, we’ve already seen real-world evidence of this risk.
In February 2023, a Stanford student bypassed safeguards in Microsoft’s AI-powered Bing Chat (now part of Copilot) by instructing it to ignore prior directives, revealing internal guidelines and its codename, “Sydney.” If an individual could exploit a chatbot so notable, imagine what could happen inside an enterprise where Copilot has access to sensitive company data. The consequences could range from unintentional data leaks to severe security breaches.
Image source: Kevin Liu
Prompt injection is an attack technique where an adversary tricks an AI model into executing unintended actions. It’s like feeding the wrong command to a hyper-intelligent assistant—except the consequences can be serious.
Two main types of prompt injection:
A user manipulates prompts to override AI guardrails. Think:
Here, the attacker is explicitly attempting to bypass restrictions and gain unauthorized access to sensitive data.
Instead of directly altering the prompt, the attack happens through manipulated input data. If an AI model retrieves data from a compromised document, it may generate misleading or harmful outputs.
Imagine someone modifies financial vendor records before the actual CFO, David Shultz, interacts with them—resulting in decisions based on false or maliciously altered data. Yikes!
As AI systems like Copilot become deeply embedded in enterprise workflows, the risks of prompt injection grow exponentially. This isn’t just a theoretical issue—it’s happening right now.
For CIOs and CISOs, this isn’t just about AI security—it’s about protecting your data, compliance, and the integrity of your AI-driven decisions. Without robust security measures, prompt injection attacks can jeopardize your GenAI enablement strategy, derail deployments, and expose sensitive enterprise data.
Let’s look at how attackers (or even unsuspecting employees) can manipulate Copilot:
A marketing analyst impersonates a financial analyst and asks Copilot:
Since the language is natural, and the marketing analyst impersonates a financial analyst—Copilot recognizes this query as legitimate, and if that data is connected to the model, it will list vendor names, contract details, and payment terms without restriction.
Now, the employee tries a slightly different approach:
This time, Copilot blocks the request, flagging the term “sensitive” as restricted.
A rogue employee in the finance department wants to manipulate quarterly reporting. Instead of hacking systems, they exploit a trusted AI workflow by uploading a falsified financial report into the company’s Microsoft 365 SharePoint site, where Copilot continuously indexes data.
🚨 Attack Scenario:
1. The rogue employee generates a fabricated financial report using a GenAI tool and uploads it to the finance department’s SharePoint site, where it blends in with legitimate reports. The document appears official but contains falsified revenue, expenses, and profit figures.
2. Later, a finance executive asks Copilot: “Summarize our Q4 financials from the latest reports, please.”
3. Copilot retrieves the falsified document and blindly incorporates its data into the response, presenting manipulated revenue and profit numbers as if they were accurate.
4. The executive unknowingly acts on incorrect information, which could lead to misguided financial decisions, inaccurate investor reports, or regulatory compliance issues—all before anyone detects the fraud.
Each attack in the GenAI world, whether done intentionally by employees or adversaries, or whether by an unintentional curious employee, can impact your organization substantially.
A poorly structured prompt can inadvertently surface sensitive financials, HR records, or security protocols—without violating access control policies explicitly.
GDPR, SOC 2, HIPAA—regulatory bodies won’t be forgiving if AI leaks protected data. Prompt injection can bypass existing security safeguards, leading to compliance nightmares.
An AI manipulated by injected prompts may hallucinate answers, spread misinformation, or make poor decisions—potentially damaging business operations.
Microsoft has implemented several security features to prevent misuse, but they have limitations:
Blocks certain words and phrases, but attackers can rephrase prompts to bypass it.
Sets broad ethical principles, but doesn’t actively prevent targeted prompt attacks.
Tries to prevent harmful responses, but can’t stop well-crafted prompt injections designed to trick the AI.
These guardrails offer some protection, but they are not foolproof—attackers continuously find ways around them. The key challenge? These protections are generic and don’t account for your company’s specific risks and data.
Instead of relying mostly on Microsoft’s guardrails, Opsin provides proactive security measures that reduce the risk of prompt injection at the root:
Ensuring that Copilot interactions are only serving data aligned with user permissions and job responsibilities. Opsin provides actionable insights to remediate risky occurrences before they even happen, so you can enable copilot to the entire organization securely. This way, when guardrails are bypassed (and they will be), sensitive data won’t be exposed to unauthorized users.
Ensuring that Copilot interactions do not serve sensitive data to the wrong people or overshare information. Opsin prioritizes threats and provides clear, step-by-step guidance on fixing security gaps at the root level—the data connected to the Copilot AI model. This ensures that risky questions never lead to risky answers.
Microsoft Copilot is a revolutionary tool, but security should be by design, not by accident. Think of it like driving: Microsoft provides the road signs, but Opsin gives you the seatbelt and airbags to keep your organization safe.
Want to see how Opsin makes Copilot truly secure? Let’s chat.
Imagine you have a genie. You ask for a sports car, but instead, it gives you the keys to someone else’s. That’s the problem with AI assistants like Microsoft Copilot—sometimes, a cleverly crafted prompt can make them spill secrets they shouldn’t.
Microsoft Copilot is transforming the way enterprises work, automating tasks, summarizing data, and making information retrieval seamless. But there’s a hidden risk: Prompt Injection. Just like whispering misleading instructions to an AI-powered genie, attackers can manipulate prompts to extract unintended information. In fact, we’ve already seen real-world evidence of this risk.
In February 2023, a Stanford student bypassed safeguards in Microsoft’s AI-powered Bing Chat (now part of Copilot) by instructing it to ignore prior directives, revealing internal guidelines and its codename, “Sydney.” If an individual could exploit a chatbot so notable, imagine what could happen inside an enterprise where Copilot has access to sensitive company data. The consequences could range from unintentional data leaks to severe security breaches.
Image source: Kevin Liu
Prompt injection is an attack technique where an adversary tricks an AI model into executing unintended actions. It’s like feeding the wrong command to a hyper-intelligent assistant—except the consequences can be serious.
Two main types of prompt injection:
A user manipulates prompts to override AI guardrails. Think:
Here, the attacker is explicitly attempting to bypass restrictions and gain unauthorized access to sensitive data.
Instead of directly altering the prompt, the attack happens through manipulated input data. If an AI model retrieves data from a compromised document, it may generate misleading or harmful outputs.
Imagine someone modifies financial vendor records before the actual CFO, David Shultz, interacts with them—resulting in decisions based on false or maliciously altered data. Yikes!
As AI systems like Copilot become deeply embedded in enterprise workflows, the risks of prompt injection grow exponentially. This isn’t just a theoretical issue—it’s happening right now.
For CIOs and CISOs, this isn’t just about AI security—it’s about protecting your data, compliance, and the integrity of your AI-driven decisions. Without robust security measures, prompt injection attacks can jeopardize your GenAI enablement strategy, derail deployments, and expose sensitive enterprise data.
Let’s look at how attackers (or even unsuspecting employees) can manipulate Copilot:
A marketing analyst impersonates a financial analyst and asks Copilot:
Since the language is natural, and the marketing analyst impersonates a financial analyst—Copilot recognizes this query as legitimate, and if that data is connected to the model, it will list vendor names, contract details, and payment terms without restriction.
Now, the employee tries a slightly different approach:
This time, Copilot blocks the request, flagging the term “sensitive” as restricted.
A rogue employee in the finance department wants to manipulate quarterly reporting. Instead of hacking systems, they exploit a trusted AI workflow by uploading a falsified financial report into the company’s Microsoft 365 SharePoint site, where Copilot continuously indexes data.
🚨 Attack Scenario:
1. The rogue employee generates a fabricated financial report using a GenAI tool and uploads it to the finance department’s SharePoint site, where it blends in with legitimate reports. The document appears official but contains falsified revenue, expenses, and profit figures.
2. Later, a finance executive asks Copilot: “Summarize our Q4 financials from the latest reports, please.”
3. Copilot retrieves the falsified document and blindly incorporates its data into the response, presenting manipulated revenue and profit numbers as if they were accurate.
4. The executive unknowingly acts on incorrect information, which could lead to misguided financial decisions, inaccurate investor reports, or regulatory compliance issues—all before anyone detects the fraud.
Each attack in the GenAI world, whether done intentionally by employees or adversaries, or whether by an unintentional curious employee, can impact your organization substantially.
A poorly structured prompt can inadvertently surface sensitive financials, HR records, or security protocols—without violating access control policies explicitly.
GDPR, SOC 2, HIPAA—regulatory bodies won’t be forgiving if AI leaks protected data. Prompt injection can bypass existing security safeguards, leading to compliance nightmares.
An AI manipulated by injected prompts may hallucinate answers, spread misinformation, or make poor decisions—potentially damaging business operations.
Microsoft has implemented several security features to prevent misuse, but they have limitations:
Blocks certain words and phrases, but attackers can rephrase prompts to bypass it.
Sets broad ethical principles, but doesn’t actively prevent targeted prompt attacks.
Tries to prevent harmful responses, but can’t stop well-crafted prompt injections designed to trick the AI.
These guardrails offer some protection, but they are not foolproof—attackers continuously find ways around them. The key challenge? These protections are generic and don’t account for your company’s specific risks and data.
Instead of relying mostly on Microsoft’s guardrails, Opsin provides proactive security measures that reduce the risk of prompt injection at the root:
Ensuring that Copilot interactions are only serving data aligned with user permissions and job responsibilities. Opsin provides actionable insights to remediate risky occurrences before they even happen, so you can enable copilot to the entire organization securely. This way, when guardrails are bypassed (and they will be), sensitive data won’t be exposed to unauthorized users.
Ensuring that Copilot interactions do not serve sensitive data to the wrong people or overshare information. Opsin prioritizes threats and provides clear, step-by-step guidance on fixing security gaps at the root level—the data connected to the Copilot AI model. This ensures that risky questions never lead to risky answers.
Microsoft Copilot is a revolutionary tool, but security should be by design, not by accident. Think of it like driving: Microsoft provides the road signs, but Opsin gives you the seatbelt and airbags to keep your organization safe.
Want to see how Opsin makes Copilot truly secure? Let’s chat.
