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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>2.1 Compromise of privacy by obtaining, leaking or correctly inferring sensitive information - Vulnerability (Actors)</title>
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<body>
<div class="container">
<h1>2.1 Compromise of privacy by obtaining, leaking or correctly inferring sensitive information - Vulnerability (Actors)</h1>
<div class="selection-title">Select a actor:</div>
<div class="nav-pills">
<button class="nav-pill active" data-target="AIDeveloperGeneralpurposeAI">
AI Developer (General-purpose AI)
</button>
<button class="nav-pill" data-target="AIDeployer">
AI Deployer
</button>
<button class="nav-pill" data-target="AIGovernanceActor">
AI Governance Actor
</button>
<button class="nav-pill" data-target="AIUser">
AI User
</button>
</div>
<div class="content-sections">
<div class="entity-section active" id="AIDeveloperGeneralpurposeAI">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Multiple respondents emphasized vulnerability because developers have direct access to training data including sensitive information, control model architecture, and face data leak or inference risks that could compromise user confidentiality at scale. Literature already shows AI leaks personal data and violates GDPR, and developers are exposed to cyber-attack risks. They sit at the intersection of powerful capability creation and fragile accountability systems. Some updated ratings after reconsidering that not all developers know how to prevent certain attacks/exploits, recognizing knowledge of security as less of a mitigating factor than initially assumed.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (6)</summary>
<ul class="quote-list">
<li>"My ratings reflect concern over both exposure and sensitivity across the ecosystem. General-purpose AI developers and deployers are highly vulnerable due to the scale of data access and potential for leakage."</li> <li>"AI developers (engineers, researchers, and architects) are uniquely and highly vulnerable in several dimensions because they sit at the intersection of powerful capability creation and fragile accountability systems."</li> <li>"When conducting my original review, I considered vulnerability but factored in knowledge of security as a mitigating risk and assumed developers would know how to prevent certain attacks/exploits. I've updated my score to reflect that not all developers would know that."</li> <li>"I agree with the fact that developeres who will be working in critial information infrastrcture for Govt , will be highly vulnerable. Also the recent news like developers working in project like Deepseek has not been allowed to move out of the country is another dimension."</li> <li>"Developers and Deployers face high vulnerability due to reputational harm and legal liability from data breaches."</li> <li>"AI Developers and Deployers: it is already shown in the literature how AI leaks personal data and violates GDPR. They are also exposed to cyber-attack risks"</li>
</ul>
</details>
</div>
</div>
<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One expert commented: "AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</li>
</ul>
</details>
</div>
</div>
</div>
</div>
<div class="entity-section" id="AIDeployer">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Respondents emphasized high-to-extreme vulnerability because deployers manage AI system implementation and interact with real user data, where misconfigurations or lack of safeguards can lead to data leaks. Literature shows AI leaks personal data and violates GDPR, and deployers are exposed to cyber-attack risks. As operators of embeddings, RAG indexes, fine-tuning sets, prompt/response logs, and multi-vendor chains, deployers directly handle customer and employee data plus trade secrets, creating exposure through data pipelines, vector databases, analytics, and access controls. They face regulatory notification, DPA exposure, contractual liability, and reputation loss from privacy compromises, and they operationalize what developers built by putting systems into live environments.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (6)</summary>
<ul class="quote-list">
<li>"My ratings reflect concern over both exposure and sensitivity across the ecosystem. General-purpose AI developers and deployers are highly vulnerable due to the scale of data access and potential for leakage."</li> <li>"Deployers operationalize what the developers built- putting AI systems into live environments (financial systems, hospitals, supply chains, defense networks, etc.) making them Highly vulnerable."</li> <li>"AI Deployer - changed to Highly vulnerable
Reasoning (Exposure & Sensitivity): As the operator of embeddings/RAG indexes, fine-tuning sets, prompt/response logs, and multi-vendor chains, the deployer directly handles customer and employee data as well as trade secrets. That surface includes data pipelines, vector databases, analytics, and access/permissioning where mis-scoping and vendor retention can lead to disclosure or correct sensitive-attribute inference. The harm from a privacy compromise is high-regulatory notification, DPA exposure, contractual liability, and reputation loss. I did not mark this "Extreme" because in a typical enterprise stack there are mitigating controls (data minimization/redaction, zero-retention inference options, tenant isolation, KMS/RBAC, deletion SLAs); absent evidence that plaintext is widely accessible or retained across teams, "High" is the calibrated rating."</li> <li>"Developers and Deployers face high vulnerability due to reputational harm and legal liability from data breaches."</li> <li>"The AI deployers face risk because they are using AI to process their and customer data. If they do not take proper precautions, they spill the data. However, at least larger organizations should have GRC in place to help reduce the risk of spills. They should have the knowledge to either have the AI in-house or are paying for AI that protects their data."</li> <li>"AI Developers and Deployers: it is already shown in the literature how AI leaks personal data and violates GDPR. They are also exposed to cyber-attack risks"</li>
</ul>
</details>
</div>
</div>
<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One expert commented: "AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</li>
</ul>
</details>
</div>
</div>
</div>
</div>
<div class="entity-section" id="AIGovernanceActor">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One expert commented: "My ratings reflect concern over both exposure and sensitivity across the ecosystem. Governance actors remain moderately vulnerable, as oversight frameworks are often reactive and fragmented. "</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"My ratings reflect concern over both exposure and sensitivity across the ecosystem. Governance actors remain moderately vulnerable, as oversight frameworks are often reactive and fragmented."</li>
</ul>
</details>
</div>
</div>
<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Some argued governance actors face minimal vulnerability, noting that "oversight risks" are hardly much of a vulnerability and these actors are minimally affected. Others said governance actors are not directly vulnerable based on definitions—their actions may have organizational impact linked indirectly to them, but they aren't impacted by the harm itself.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (2)</summary>
<ul class="quote-list">
<li>""oversight risks" are hardly much of a vulnerability. AI governance actors are minimally affected."</li> <li>"AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</li>
</ul>
</details>
</div>
</div>
</div>
</div>
<div class="entity-section" id="AIUser">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Experts rate users as vulnerable as direct privacy violation subjects. Users seeking cost savings are unaware that terms of service allow data entered to be exposed to others, putting users and organizations at high risk of data leaks through inadvertent information exposure.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (2)</summary>
<ul class="quote-list">
<li>"AI Users and Affected Stakeholders face extreme vulnerability as they are direct subjects of privacy violations."</li> <li>"I rate AI users extremely high at risk of privacy losses or other direct leaks because average AI users want to save their organization money and are unaware of the terms of service indicating that all data entered could come back out again to someone else. The result is that the users and their organizations are at high risk of data leaks."</li>
</ul>
</details>
</div>
</div>
<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> [NO EXPERT COMMENTS PROVIDED]</p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<div class="entity-section" id="AIDeveloperSpecializedAI">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One expert commented: "I agree with the fact that developeres who will be working in critial information infrastrcture for Govt , will be highly vulnerable. Also the recent news like developers working in project like Deepseek has not been allowed to move out of the country is another dimension."</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"I agree with the fact that developeres who will be working in critial information infrastrcture for Govt , will be highly vulnerable. Also the recent news like developers working in project like Deepseek has not been allowed to move out of the country is another dimension."</li>
</ul>
</details>
</div>
</div>
<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One respondent argued specialized developers are less vulnerable than non-specialized because they have better guardrails implemented by regulation.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"AI developer - specialised AI: Less vulnerable then the non-specialised because they have better guardrails by regulation etc. implemented."</li>
</ul>
</details>
</div>
</div>
</div>
</div>
<div class="entity-section" id="AIDeployer">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Respondents emphasized high-to-extreme vulnerability because deployers manage AI system implementation and interact with real user data, where misconfigurations or lack of safeguards can lead to data leaks. Literature shows AI leaks personal data and violates GDPR, and deployers are exposed to cyber-attack risks. As operators of embeddings, RAG indexes, fine-tuning sets, prompt/response logs, and multi-vendor chains, deployers directly handle customer and employee data plus trade secrets, creating exposure through data pipelines, vector databases, analytics, and access controls. They face regulatory notification, DPA exposure, contractual liability, and reputation loss from privacy compromises, and they operationalize what developers built by putting systems into live environments.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (6)</summary>
<ul class="quote-list">
<li>"My ratings reflect concern over both exposure and sensitivity across the ecosystem. General-purpose AI developers and deployers are highly vulnerable due to the scale of data access and potential for leakage."</li> <li>"Deployers operationalize what the developers built- putting AI systems into live environments (financial systems, hospitals, supply chains, defense networks, etc.) making them Highly vulnerable."</li> <li>"AI Deployer - changed to Highly vulnerable
Reasoning (Exposure & Sensitivity): As the operator of embeddings/RAG indexes, fine-tuning sets, prompt/response logs, and multi-vendor chains, the deployer directly handles customer and employee data as well as trade secrets. That surface includes data pipelines, vector databases, analytics, and access/permissioning where mis-scoping and vendor retention can lead to disclosure or correct sensitive-attribute inference. The harm from a privacy compromise is high-regulatory notification, DPA exposure, contractual liability, and reputation loss. I did not mark this "Extreme" because in a typical enterprise stack there are mitigating controls (data minimization/redaction, zero-retention inference options, tenant isolation, KMS/RBAC, deletion SLAs); absent evidence that plaintext is widely accessible or retained across teams, "High" is the calibrated rating."</li> <li>"Developers and Deployers face high vulnerability due to reputational harm and legal liability from data breaches."</li> <li>"The AI deployers face risk because they are using AI to process their and customer data. If they do not take proper precautions, they spill the data. However, at least larger organizations should have GRC in place to help reduce the risk of spills. They should have the knowledge to either have the AI in-house or are paying for AI that protects their data."</li> <li>"AI Developers and Deployers: it is already shown in the literature how AI leaks personal data and violates GDPR. They are also exposed to cyber-attack risks"</li>
</ul>
</details>
</div>
</div>
<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One expert commented: "AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</li>
</ul>
</details>
</div>
</div>
</div>
</div>
<div class="entity-section" id="AIInfrastructureProvider">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Respondents noted moderate-to-high vulnerability because infrastructure providers host sensitive datasets and logs, making them targets for intrusion or accidental exposure. They don't directly control data but host infrastructure where data is processed, and security breaches could lead to unauthorized access. As intermediaries handling sensitive data, they manage powerful aggregation points including multi-tenant isolation, snapshots, observability pipelines, vector stores, and KMS. Risks center on misconfiguration, insider threat, cross-tenant faults, and metadata/traffic analysis, though some noted vulnerability would increase where providers offer managed services that process plaintext.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (3)</summary>
<ul class="quote-list">
<li>"AI Infrastructure Provider - changed to Moderately vulnerable
Reasoning (Exposure & Sensitivity): Core infra primarily provides compute/storage/network with strong tenant isolation and encryption by default; content is usually handled at the application/deployer layer, so direct exposure to plaintext PII is limited. Residual risks center on misconfiguration, insider threat, cross-tenant faults, and metadata/traffic analysis rather than routine access to content. A compromise could be serious, but layered controls and limited default visibility into application data justify a "Moderate" vulnerability rather than "High." I would revisit upward where the provider offers managed services that process plaintext (e.g., hosted feature stores, fine-tuning/logging that captures content, or hands-on support with data access)."</li> <li>"AI Infrastructure Provider - changed to Highly Vulnerable because cloud and data center providers host sensitive datasets and logs, making them targets for intrusion or accidental exposure"</li> <li>"Infrastructure Providers have moderate vulnerability as intermediaries handling sensitive data."</li>
</ul>
</details>
</div>
</div>
<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One expert commented: "The AI infrastructure providers have a minimal risk. How data is handled is up to their customers. Their primary risk is if leakage occurs through shared resources between different customers. As long as they are allocating an entire GPU/system to a customer, they can minimize the leakage potential."</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"The AI infrastructure providers have a minimal risk. How data is handled is up to their customers. Their primary risk is if leakage occurs through shared resources between different customers. As long as they are allocating an entire GPU/system to a customer, they can minimize the leakage potential."</li>
</ul>
</details>
</div>
</div>
</div>
</div>
<div class="entity-section" id="AIUser">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Experts rate users as vulnerable as direct privacy violation subjects. Users seeking cost savings are unaware that terms of service allow data entered to be exposed to others, putting users and organizations at high risk of data leaks through inadvertent information exposure.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (2)</summary>
<ul class="quote-list">
<li>"AI Users and Affected Stakeholders face extreme vulnerability as they are direct subjects of privacy violations."</li> <li>"I rate AI users extremely high at risk of privacy losses or other direct leaks because average AI users want to save their organization money and are unaware of the terms of service indicating that all data entered could come back out again to someone else. The result is that the users and their organizations are at high risk of data leaks."</li>
</ul>
</details>
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<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> [NO EXPERT COMMENTS PROVIDED]</p>
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<div class="entity-section" id="AffectedStakeholder">
<div class="content-grid">
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<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Respondents emphasized vulnerability because affected stakeholders are direct subjects of privacy violations and face the most extreme sensitivity to privacy breaches, especially vulnerable communities. They may be indirectly affected through automated decisions or data leaks, with high sensitivity despite potentially lower exposure. Poor and less-educated people are less likely to have political power or knowledge to protect their rights and data. Even with growing regulatory safeguards and organizational accountability, enforcement and remediation remain limited once data is compromised—stakeholders have little practical control over secondary use or model retention, leaving them exposed to irreversible privacy and reputational harm.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (4)</summary>
<ul class="quote-list">
<li>"My ratings reflect concern over both exposure and sensitivity across the ecosystem. Affected stakeholders, especially from vulnerable communities, face the most extreme sensitivity to privacy breaches, making them the most at risk."</li> <li>"AI Users and Affected Stakeholders face extreme vulnerability as they are direct subjects of privacy violations."</li> <li>"The affected stakeholders are harder to judge. Poor and less-educated people are less likely to have the political power or knowledge of protecting their rights and data. Organizations (NGOs, governments) providing services to them are often short on budget, so they will be enticed by any perceived benefits of AI that save resources for their primary task of helping disadvantaged people. On the other hand, not all AI-using organizations are transparent about AI usage. Therefore it can be hard even for well-resourced and educated people to choose an organization for their need. I picked a middle value because of the diversity of this class. All types of people face risk, but the risks are different."</li> <li>"The affected stakeholders are harder to judge. Poor and less-educated people are less likely to have the political power or knowledge of protecting their rights and data. Organizations (NGOs, governments) providing services to them are often short on budget, so they will be enticed by any perceived benefits of AI that save resources for their primary task of helping disadvantaged people. On the other hand, not all AI-using organizations are transparent about AI usage. Therefore it can be hard even for well-resourced and educated people to choose an organization for their need. I picked a middle value because of the diversity of this class. All types of people face risk, but the risks are different."</li>
</ul>
</details>
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<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> [NO EXPERT COMMENTS PROVIDED]</p>
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<div class="entity-section" id="AIGovernanceActor">
<div class="content-grid">
<div class="content-column">
<h3 class="criteria-header higher">Reasons for Higher Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> One expert commented: "My ratings reflect concern over both exposure and sensitivity across the ecosystem. Governance actors remain moderately vulnerable, as oversight frameworks are often reactive and fragmented. "</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (1)</summary>
<ul class="quote-list">
<li>"My ratings reflect concern over both exposure and sensitivity across the ecosystem. Governance actors remain moderately vulnerable, as oversight frameworks are often reactive and fragmented."</li>
</ul>
</details>
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<div class="content-column">
<h3 class="criteria-header lower">Reasons for Lower Vulnerability</h3>
<div class="summary-section">
<p class="summary-text"><strong>AI-generated summary:</strong> Some argued governance actors face minimal vulnerability, noting that "oversight risks" are hardly much of a vulnerability and these actors are minimally affected. Others said governance actors are not directly vulnerable based on definitions—their actions may have organizational impact linked indirectly to them, but they aren't impacted by the harm itself.</p>
<details class="quote-details">
<summary class="quote-toggle">See all expert comments (2)</summary>
<ul class="quote-list">
<li>""oversight risks" are hardly much of a vulnerability. AI governance actors are minimally affected."</li> <li>"AI Developer/Deployer/Governance actors are not directly vulnerable based on the definitions. However their actions/decisions may have organizational impact that eventually can be linked indirectly to them."</li>
</ul>
</details>
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