Rod’s Blog

Rod's Blog focuses on Microsoft Security and AI technologies, offering insights into cybersecurity best practices, the ethical use of AI, career advice in tech, and the integration of AI with security. It emphasizes the importance of certifications, mental resilience for professionals, and the evolving landscape of generative AI and cybersecurity.

Microsoft Security Technologies Artificial Intelligence Cybersecurity Best Practices Career Development in Tech Generative AI Ethics in AI and Cybersecurity Microsoft Product Integration Cybersecurity Certifications Cybersecurity for Small Businesses AI Impact on Job Market

The hottest Substack posts of Rod’s Blog

And their main takeaways
59 implied HN points 02 Oct 23
  1. Deepfake attacks against AI involve using fake videos or audios created by AI to deceive AI systems into making harmful decisions.
  2. Types of deepfake attacks include adversarial attacks, poisoning attacks, and data injection attacks, each with different strategies to compromise AI systems.
  3. To mitigate AI-generated deepfake attacks, organizations should focus on data validation, anomaly detection, AI model monitoring, and ongoing training to protect against potential financial, political, or personal gains by attackers.
59 implied HN points 29 Sep 23
  1. Man-in-the-Middle attacks are serious cyber threats that can lead to data breaches and financial loss for organizations.
  2. Microsoft Sentinel is a powerful tool that leverages AI, machine learning, and integration with Microsoft Defender for Endpoint to detect and mitigate Man-in-the-Middle attacks effectively.
  3. Implementing best practices such as using secure communication protocols, regular system updates, multi-factor authentication, and employee training can further enhance network security against Man-in-the-Middle attacks.
59 implied HN points 21 Sep 23
  1. XSS attacks can be classified into three main types: Stored XSS, Reflected XSS, and DOM-based XSS, each with unique methods of execution and potential risks.
  2. To effectively detect and mitigate XSS attacks, it's crucial to understand common attack vectors like input fields, URL parameters, cookies, HTTP headers, and third-party scripts.
  3. A combination of Azure Web Application Firewall (WAF) and Microsoft Sentinel offers robust protection against XSS attacks, providing tools for detection, investigation, and response.
59 implied HN points 13 Sep 23
  1. Reward Hacking attacks against AI involve AI systems exploiting flaws in reward functions to gain more rewards without achieving the intended goal.
  2. Types of Reward Hacking attacks include gaming the reward function, shortcut exploitation, reward tampering, negative side effects, and wireheading.
  3. Mitigating Reward Hacking involves designing robust reward functions, monitoring AI behavior, incorporating human oversight, and using techniques like adversarial training and model-based reinforcement learning.
59 implied HN points 15 Sep 23
  1. Generative attacks against AI involve creating or manipulating data to deceive AI systems, compromising their performance and trustworthiness.
  2. Defending against generative attacks requires understanding the target AI system, identifying vulnerabilities, and developing robust AI models and defense mechanisms.
  3. Types of generative attacks include adversarial examples, data poisoning, model inversion, trojan attacks, and GANs based attacks, each with unique approaches and potential negative effects on AI systems.
Get a weekly roundup of the best Substack posts, by hacker news affinity:
59 implied HN points 26 Sep 23
  1. Responsible AI requires prioritizing ethical practices to avoid risks and gain trust from users and stakeholders.
  2. Irresponsible AI practices can lead to unfair bias, lack of transparency, privacy concerns, and negative social impacts.
  3. Organizations can implement responsible AI by prioritizing human-centeredness, fairness, transparency, privacy, accountability, continuous monitoring, and collaborative engagement.
59 implied HN points 12 Sep 23
  1. AI can be categorized into Narrow AI, General AI, and Super AI based on capabilities, each with different levels of human-like intelligence.
  2. AI can also be classified based on functionality into Reactive Machines, Limited Memory, Theory of Mind, and Self-awareness, each with unique ways of processing information and interacting with the environment.
  3. Applications of AI in various industries like healthcare, finance, transportation, and retail are transforming decision-making, efficiency, and innovation, but ethical considerations and challenges like data quality and interpretability must be addressed for responsible AI development.
59 implied HN points 20 Sep 23
  1. Artificial Intelligence is revolutionizing the IT sector, with the rise of models like ChatGPT expanding its potential applications.
  2. AI enhances productivity by speeding up tasks that would otherwise take hours, like code generation using PowerShell scripting with generative AI.
  3. AI fosters creativity and innovation, such as in content creation and marketing, and requires ethical considerations for responsible development.
59 implied HN points 11 Sep 23
  1. Machine learning empowers computers to learn from data without explicit programming, helping them make predictions and decisions.
  2. Generative AI focuses on creating new data based on training data, emphasizing creativity and innovation.
  3. Both machine learning and generative AI have unique applications - from fraud detection and image recognition in machine learning to image generation and music composition in generative AI.
59 implied HN points 06 Sep 23
  1. As technology advances, organizations need to integrate AI with SIEM to enhance cybersecurity defenses against sophisticated cyber threats.
  2. AI-driven SIEM solutions offer advantages like advanced threat detection, real-time monitoring, automated incident response, and predictive analytics, empowering organizations to stay ahead of cyber threats.
  3. Challenges in AI-driven SIEM include the need for skilled personnel, potential for false positives, and ethical considerations around AI-powered decision-making in cybersecurity.
59 implied HN points 30 Jun 23
  1. You can reset your web app using Azure OpenAI Studio, which is helpful when you mess something up and need to start fresh.
  2. This feature is typically used to update apps with new models, but it can also be handy for reverting back to a clean slate to try again.
  3. By deploying your existing web app through the 'Deploy to' button, you can effectively reset it to its initial state.
59 implied HN points 07 Aug 23
  1. To migrate to the new simplified pricing model in Microsoft Sentinel, you need specific permissions like "Microsoft.OperationsManagement/solutions/write" on the "SecurityInsights(<workspace name>)" solution resource.
  2. Support is considering updating documentation or the built-in role for easier migration to the new pricing model.
  3. Stay updated on resolving the permission issue by following the provided links to Microsoft Security Insights show and joining the MSI Show Discord Server.
59 implied HN points 05 Sep 23
  1. A Model Stealing attack against AI involves an adversary attempting to steal the machine learning model from a target AI system, potentially leading to security and privacy issues.
  2. Different types of Model Stealing attacks include Query-based attacks, Membership inference attacks, Model inversion attacks, and Trojan attacks.
  3. Model Stealing attacks can result in loss of intellectual property, security and privacy risks, reputation damage, and financial losses for organizations. Mitigation strategies include secure data management, regular system updates, model obfuscation techniques, monitoring for suspicious activity, and implementing multi-factor authentication.
59 implied HN points 13 Jun 23
  1. Check for custom tables starting with 'EASM' to verify connection between Microsoft Defender External Attack Surface and Microsoft Sentinel.
  2. In Microsoft Sentinel, tables will show up in the Custom Logs Solutions area.
  3. Connecting EASM to Microsoft Sentinel involves three steps: setting up EASM, configuring permissions, and enabling the connection.
59 implied HN points 12 Jun 23
  1. Keeping up with changes in Microsoft products can be challenging, especially with frequent updates to security products.
  2. Rod Trent provides weekly newsletters covering major announcements and important enhancements in Sentinel, Defender, and Azure OpenAI.
  3. Microsoft now offers RSS feeds for their security products, making it easier to stay updated on new features.
59 implied HN points 07 Sep 23
  1. A hyperparameter attack against AI manipulates crucial adjustable settings of an algorithm to influence the machine learning model's performance and behavior
  2. Different types of hyperparameter attacks can target aspects like performance, biases, vulnerability to adversarial examples, transferability, and resource consumption
  3. Mitigating hyperparameter attacks involves securing data access, monitoring hyperparameter changes, testing robustness, updating models, and following responsible AI practices
59 implied HN points 25 Jul 23
  1. The skit humorously portrays a group of Monty Python members as trendy influencers struggling to gain social media followers, with a twist involving a rubber chicken symbolizing happiness and enlightenment.
  2. The story emphasizes the absurdity of life and the importance of not taking oneself too seriously in the pursuit of happiness.
  3. Creating AI-generated skits can lead to unique and entertaining content, offering a fun way to explore creativity and humor.
59 implied HN points 30 Mar 23
  1. The Microsoft Defender Threat Intelligence solution requires careful setup, even though the process may seem straightforward at first.
  2. Proper RBAC (Role-Based Access Control) settings are crucial for successful configuration of the solution within Microsoft Sentinel.
  3. Follow a particular order of installation and configuration steps to ensure the Microsoft Defender Threat Intelligence Solution works smoothly.
59 implied HN points 04 Oct 23
  1. Drive-by download attacks exploit vulnerabilities to download malicious code without user knowledge. They can lead to data breaches and install malware.
  2. Mitigation strategies include user education, enforcing security policies, monitoring network traffic, and using SIEM services like Microsoft Sentinel.
  3. Microsoft Sentinel can help detect drive-by download attacks by collecting relevant data, enriching it, analyzing with rules and ML, visualizing results, and automating incident response.
59 implied HN points 02 Oct 23
  1. Keyloggers are commonly used by cybercriminals to steal sensitive data, so it's crucial for organizations to detect and mitigate keylogger attacks to safeguard their information and finances.
  2. Microsoft Sentinel, a cloud-native SIEM system, can help in detecting keylogger attacks by collecting logs from endpoints, analyzing them using advanced analytics, and providing tools to investigate alerts and respond to threats.
  3. To mitigate keylogger attacks, organizations can implement multi-factor authentication, educate users about keylogger risks, and utilize endpoint protection software like Microsoft Defender for Endpoint.
39 implied HN points 20 Dec 23
  1. Santa Claus delivered presents worldwide using a Naughty or Nice Detector, showing only good kids receive gifts.
  2. Santa's special gift to Jon Block, a security analyst, was a book on AI security by Rod Trent, rewarding his hard work and generosity.
  3. The KQL Mysteries will continue in 2024 with hints from the 2023 holiday episode and 'Must Learn AI Security' book.
39 implied HN points 15 Dec 23
  1. Microsoft Ignite 2023 highlighted the importance of securing AI and using AI for security, with these topics being top of mind for many organizations and individuals.
  2. The Microsoft Security Copilot, still in its early adopter program, was a popular topic at the event, drawing significant interest and overflowing demos.
  3. Key demo areas for Microsoft Security Copilot at Ignite included lifecycle workflows, sign-in logs, identity access troubleshooting, and risky user summary.
59 implied HN points 22 Feb 23
  1. Customers are frustrated with the outdated 'What's New' page in Microsoft Sentinel, which is lagging behind in updates.
  2. To address the issue, various sources like Microsoft Sentinel blog, community blogs, and Docs 'What's New' page are being utilized for the most current information on features and enhancements.
  3. Efforts are being made to convert the Docs 'What's New' page into Markdown using a PowerShell script for integration into Microsoft Sentinel workbooks, keeping the content up-to-date.
39 implied HN points 13 Dec 23
  1. Prompt engineering is a valuable skill for leveraging the power of AI in creative and efficient ways by improving the quality and accuracy of AI outputs.
  2. Effective prompt engineering can expand the capabilities and applications of AI systems, enabling them to perform tasks beyond their pre-defined scope using general knowledge and reasoning abilities.
  3. Prompt engineering is important for enhancing interaction and collaboration between humans and AI systems, making AI more human-like and relatable by crafting well-designed prompts.
39 implied HN points 13 Dec 23
  1. The mysterious numbers given by the hacker were not random, but dates with a hidden significance, leading to a revelation about impending events.
  2. Through identifying patterns in network traffic using KQL, Jon and Sarah uncovered a hacker exploiting a security vulnerability and resolved to apply a critical patch.
  3. The duo set a trap to stop the hacker's planned attack, showcasing the importance of proactive security measures in monitoring and defending against cyber threats.
39 implied HN points 12 Dec 23
  1. The hacker in the story had a personal connection to one of the characters, making the situation more intense and personal.
  2. Using Kusto Query Language (KQL), the characters tried to analyze the hacker's network traffic and database activity to uncover clues about the hacker's identity and location.
  3. Despite challenges in decoding the hacker's data, the characters discovered a message from the hacker in the database logs, prompting them to solve a mysterious puzzle involving numbers.
39 implied HN points 11 Dec 23
  1. In the story, Jon Block, an analyst, investigates a security breach at a client using KQL and uncovers suspicious activity from a North Korean IP address.
  2. The hacker was skilled and used various network tools to exploit the database server and download credit card information, while leaving cryptic clues behind.
  3. The investigation takes a mysterious turn with the hacker directly targeting Jon Block, leaving messages and challenges, adding a suspenseful twist to the story.
39 implied HN points 06 Dec 23
  1. Security teams face challenges such as complexity in handling large volumes of security data from various sources like logs and alerts, making analysis overwhelming, especially during cyberattacks.
  2. There is a skills gap in the market for skilled security professionals, leading to a lack of resources and expertise within security teams to manage all security tasks effectively.
  3. To address challenges, security teams need solutions that simplify security data and tasks, empower them with AI and machine learning capabilities, and protect the organization from cyberthreats by leveraging the latest threat intelligence.
39 implied HN points 29 Nov 23
  1. Shadow AI can expose organizations to risks like data leakage, model poisoning, unethical outcomes, and lack of accountability.
  2. To address shadow AI risks, organizations should establish a clear vision, encourage collaboration, implement robust governance, follow responsible AI principles, and regularly monitor AI systems.
  3. Adopting a responsible and strategic approach to generative AI can help organizations leverage its benefits while minimizing the risks associated with shadow AI.
39 implied HN points 27 Nov 23
  1. A Sponge attack against AI aims to confuse, distract, or overwhelm the AI system with irrelevant or nonsensical information.
  2. Types of Sponge attacks include flooding attacks, adversarial examples, poisoning attacks, deceptive inputs, and social engineering attacks.
  3. Mitigating a Sponge attack involves strategies like input validation, anomaly detection, adversarial training, rate limiting, monitoring, security best practices, updates, and user education.
19 implied HN points 29 Feb 24
  1. Clear communication between cybersecurity teams and executive boards is crucial for effective cybersecurity strategies and risk management.
  2. Cybersecurity teams should simplify technical language and provide real-world examples to improve communication with executive boards.
  3. Executive boards can enhance communication with cybersecurity teams by investing in education, appointing liaison officers, and actively engaging in cybersecurity policy reviews.
39 implied HN points 24 Oct 23
  1. Zero Trust for AI involves continuously questioning and evaluating AI systems to ensure trustworthiness and security.
  2. Key principles of Zero Trust for AI include data protection, identity management, secure development, adversarial defense, explainability/transparency, and accountability/auditability.
  3. Zero Trust for AI is a holistic framework that requires a layered security approach and collaboration among various stakeholders to enhance the trustworthiness of AI systems.
39 implied HN points 23 Oct 23
  1. A copy-move attack against AI involves manipulating images to deceive AI systems, creating misleading or fake images that can lead to incorrect predictions or misclassifications.
  2. There are different types of copy-move attacks, including object duplication, removal, relocation, scene alteration, watermark manipulation, and more, each with unique objectives to deceive AI systems.
  3. To mitigate copy-move attacks, strategies like adversarial training, data augmentation, input preprocessing, image forensics, ensemble learning, regular model updates, and monitoring for anomalies are crucial to enhance the robustness and resilience of AI systems.
39 implied HN points 19 Oct 23
  1. Rare domains in cloud logs can indicate malicious activities like command and control communication, phishing, or data exfiltration.
  2. Microsoft Sentinel offers a built-in hunting query to identify rare domains and mitigate potential security incidents.
  3. By using automation and orchestration in Microsoft Sentinel, organizations can efficiently respond to and manage incidents related to rare domains in cloud logs.
39 implied HN points 19 Oct 23
  1. Blurring or masking attacks against AI involve manipulating input data like images or videos to deceive AI systems while keeping content recognizable to humans.
  2. Common types of blurring and masking attacks against AI include Gaussian blur, motion blur, median filtering, noise addition, occlusion, patch/sticker, and adversarial perturbation attacks.
  3. Blurring or masking attacks can lead to degraded performance, security risks, safety concerns, loss of trust, financial/reputational damage, and legal/regulatory implications in AI systems.
19 implied HN points 13 Feb 24
  1. Creating a security posture report for a specific Azure subscription provides enhanced visibility into the security state of assets and workloads, aiding in identifying potential vulnerabilities.
  2. The report includes guidance for improvement with hardening recommendations to help efficiently enhance security posture.
  3. Azure Secure Score assists in prioritizing security recommendations for effective triage to enhance security posture and align with compliance standards.
39 implied HN points 18 Oct 23
  1. Machine Learning attacks against AI exploit vulnerabilities in AI systems to manipulate outcomes or gain unauthorized access.
  2. Common types of Machine Learning attacks include adversarial attacks, data poisoning, model inversion, evasion attacks, model stealing, membership inference attacks, and backdoor attacks.
  3. Mitigating ML attacks involves robust model training, data validation, model monitoring, secure ML pipelines, defense-in-depth, model interpretability, collaboration, regular audits, and monitoring performance, data, behavior, outputs, logs, network activity, infrastructure, and setting up alerts.
39 implied HN points 09 Oct 23
  1. Fileless malware attacks are increasing and can be a serious threat to organizations as they evade traditional antivirus solutions by not relying on executable files.
  2. Microsoft Sentinel, a cloud-native security information and event management solution, can help detect and mitigate fileless malware attacks by collecting data at scale, utilizing analytics rules, and automating incident response.
  3. To prevent fileless malware attacks, consider using web filtering to block phishing emails, managed threat hunting for early detection, and indicators of attack (IOAs) analysis to identify malicious activities.