Identifying Hidden Security Risks in AWS

I recently completed a client's AWS infrastructure audit. The issues that uncovered are surprisingly common. Here's what I found: 𝟭. 𝗨𝗻𝗲𝗻𝗰𝗿𝘆𝗽𝘁𝗲𝗱 𝗘𝗕𝗦 𝗩𝗼𝗹𝘂𝗺𝗲𝘀   Data at rest was not encrypted, posing a significant security risk. 𝟮. 𝗖𝗹𝗼𝘂𝗱𝗧𝗿𝗮𝗶𝗹 𝗗𝗶𝘀𝗮𝗯𝗹𝗲𝗱   The account lacked crucial audit logs, limiting visibility into account activities. 𝟯. 𝗣𝘂𝗯𝗹𝗶𝗰 𝗦𝟯 𝗕𝘂𝗰𝗸𝗲𝘁𝘀   Several S3 buckets were publicly accessible, potentially exposing sensitive data. 𝟰. 𝗦𝗦𝗛 (𝗣𝗼𝗿𝘁 𝟮𝟮) 𝗢𝗽𝗲𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗪𝗼𝗿𝗹𝗱   Unrestricted SSH access increased the attack surface unnecessarily. 𝟱. 𝗩𝗣𝗖 𝗙𝗹𝗼𝘄 𝗟𝗼𝗴𝘀 𝗗𝗶𝘀𝗮𝗯𝗹𝗲𝗱   Network traffic insights were missing, hampering security analysis capabilities. 𝟲. 𝗗𝗲𝗳𝗮𝘂𝗹𝘁 𝗩𝗣𝗖 𝗦𝘁𝗶𝗹𝗹 𝗶𝗻 𝗨𝘀𝗲   The default VPC was being used, often lacking proper segmentation and security controls. These findings aren't unusual. Many organizations, from startups to enterprises, overlook these aspects of AWS security and best practices. That's why doing regular AWS account audits are crucial. They help identify potential vulnerabilities before they become problems. 𝗞𝗲𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀 𝗮𝗻𝗱 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: 1. Encrypt data at rest: Enable default EBS encryption at the account level. 2. Implement comprehensive logging: Enable CloudTrail across all regions and set up alerts. 3. Restrict public access: Use S3 Block Public Access at the account level and audit existing buckets. 4. Use modern, secure access methods: Implement AWS Systems Manager Session Manager instead of open SSH. 5. Enable network monitoring: Turn on VPC Flow Logs and set up automated analysis. 6. Design your network architecture intentionally: Create custom VPCs with proper security controls. By addressing these common issues, you significantly enhance your AWS security posture. It's not about perfection, but continuous improvement. When's the last time you audited your AWS environment?

As a SOC engineer, your responsibility is to enhance detection and prevention controls within your environment. However, this cannot be achieved without first identifying the blind spots in your environment. Consider a scenario where an attacker gains access to your AWS account and attempts to create a Lambda function, then modifies its resource-based policy to allow lambda:InvokeFunction from an external AWS account. Would your current setup be able to prevent or detect such a backdoor? To address this, it might be helpful to break the issue down into several sub-questions, such as: 1-Which IAM roles or users are authorized to create and update Lambda functions? 2-Do you have any SCPs or restrictions that prevent Lambda functions from being modified to allow invocation from external AWS accounts? 3-Is there an approval process, policy, or exception-handling procedure in place for such cases? 4-Can you list all Lambda functions that are configured to be invoked externally? 5-Are you able to differentiate between internal and external Lambda invocations? 6-Would you receive a notification in the event of an external invocation? Is IAM Access Analyzer enabled in your environment? 7-Do you have an incident response playbook for handling such scenarios? This highlights the power of purple teaming activities in an AWS environment. By simulating real-world attack scenarios like this, you can proactively identify blind spots, enhance your detection and prevention mechanisms, and improve critical aspects such as change management processes, incident response playbooks, IAM roles, SCP policies, IAM Access Analyzer configurations, and logging. #PurpleTeaming #Backdoor #CloudSecurity #AWS

“READ-ONLY access”—sounds safe, right? After all, it’s just viewing, not changing anything. But the cloud is complicated and in AWS, READ-ONLY access can still lead to significant risks, depending on the security posture of your environment. I’m not saying there’s no place for READ-ONLY permissions. There certainly are, but it’s crucial to recognize that this privilege is not without its dangers. Consider the following potential risks with AWS’s "ReadOnlyAccess" managed IAM policy that could lead to things like secrets discovery, privilege escalation, compromise, and more: 🔴 Enumerate all EC2s and their properties, including UserData scripts 🔴 Enumerate all IAM users, roles, identity providers, and review their trust policies 🔴 Enumerate environment variables in Lambda, ECS, Lightsail containers, Sagemaker 🔴 Enumerate SSM documents 🔴 Read and decrypt SSM Parameter secrets 🔴 And more… #aws #awssecurity #cloudsecurity #cloudengineering #iam #cybersecurity

🔭A vulnerability was recently discovered in HTTP requests within web applications managing AWS infrastructure. These vulnerabilities could potentially allow attackers to capture access keys and session tokens (which are often temporarily shared with external users, who can upload device logs to CloudWatch), enabling unauthorized access to backend IoT endpoints and CloudWatch instances. What is at risk: 📛Attackers can intercept these credentials in clear text, potentially uploading false logs or sending MQTT messages to IoT endpoints. This not only compromises data integrity but also increases operational costs through fraudulent activities. 📞The PoC showed a peer-to-peer screen sharing application built on AWS that HTTP made requests to specific endpoints that could expose sensitive credentials. 🗒Two unique endpoints were found: ‘/createsession’ and ‘/cloudwatchupload’. When a request was sent to the ‘/createsession’, the web application responded with access keys and session tokens corresponding to an AWS IOT endpoint. These keys were successfully used to send MQTT messages to the AWS IOT endpoint. 🛠Recommended Actions: Data should be routed through an internal server that validates and securely forwards it to AWS services. Implementing centralized auditing, logging, and rate limiting will further enhance security. This case serves as a stark reminder of the ongoing risks and design flaws prevalent in integrating web applications with backend cloud services. #CyberSecurity #AWS #InfoSec #CloudSecurity #DataProtection

A few months ago, we found a malicious AWS CloudFormation template trying to breach a customer's AWS account. It was disguised as “AWS Support for Fargate” Here’s what it’s really up to: 1. Grants itself administrator-level permissions via a fake support IAM role 2. Deploys a lambda function (in-line) to exfiltrate role ARN to an external API Gateway endpoint 3. Invoke itself using AWS CloudFormation CustomResource 📘 Blue team tips - Always review the IAM roles, policies, and external calls in any template. - Use the IAM Access Analyzer to verify external trust relationships - Don’t blindly trust anything labeled “AWS Support” — verify it first! - Report to AWS Security teams ASAP 📕 Red team tips - The malicious actor is identified by the AWS account ID in the AssumeRole policy. - Consider flooding the API endpoint with randomly generated payloads using fake IAM role ARNs.

Imagine waking up to a $15,000 AWS bill for an S3 bucket that was sitting empty. This isn't a hypothetical horror story. It just happened to a founder who shared their experience on Reddit. His site was targeted by a DDoS attack. He thought it was under control after shutting down the database. He was wrong. The attacker shifted focus to the S3 bucket, hammering it with requests for 3 days straight. By the time the bill arrived, 160TB of data egress had been clocked. The price tag? $15,000. The scary part is how many solo founders and small teams are sitting on this exact "Denial of Wallet" risk. If someone knows your bucket name, they can run up your bill without ever gaining access to your data. AWS has started rolling out changes to stop charging for certain unauthorized 403 errors, but you cannot rely on defaults to protect your business. As a founder, you have enough to worry about without a surprise bill that could wipe out your runway. To protect your S3 buckets today: • Use CloudFront with Origin Access Control (OAC) to keep your S3 bucket hidden from the public internet. • Set up AWS Budgets and Cost Anomaly Detection to alert you the second spending deviates from the norm. • Avoid using predictable names for your buckets like "company-backups" or "prod-data" which are easy for attackers to guess. • Enable S3 Storage Lens or CloudWatch metrics to monitor request patterns in real-time. • Use rate limits wherever possible. Cloud scalability is useful, but without guardrails, it is a liability. Take 10 minutes today to audit your S3 permissions. It might save you $15,000 tomorrow. PS: Have you ever had a "sticker shock" moment with your cloud bill?

Most cloud security architectures look mature on paper. Until scale exposes the hidden gaps. That is the real challenge enterprises are facing in 2026. Modern cloud environments are expanding faster than governance models can adapt. And many organisations still focus on external threats while internal architectural weaknesses compound silently. The strongest Security Architects are paying attention to a different category of risk: Operational blind spots. → 𝐈𝐝𝐞𝐧𝐭𝐢𝐭𝐲 𝐭𝐫𝐮𝐬𝐭 𝐞𝐱𝐩𝐥𝐨𝐬𝐢𝐨𝐧 ↳ Machine identities now outnumber human users → 𝐄𝐚𝐬𝐭-𝐰𝐞𝐬𝐭 𝐭𝐫𝐚𝐟𝐟𝐢𝐜 𝐢𝐧𝐯𝐢𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲 ↳ Internal lateral movement remains poorly monitored → 𝐒𝐡𝐚𝐝𝐨𝐰 𝐀𝐏𝐈 𝐞𝐱𝐩𝐨𝐬𝐮𝐫𝐞 ↳ Unknown APIs are becoming hidden attack surfaces → 𝐅𝐫𝐚𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐬𝐞𝐜𝐫𝐞𝐭𝐬 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 ↳ Credential sprawl creates invisible privilege risk → 𝐀𝐈 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐠𝐚𝐩𝐬 ↳ Vector databases and agent permissions introduce new trust boundaries → 𝐂𝐥𝐨𝐮𝐝-𝐧𝐚𝐭𝐢𝐯𝐞 𝐰𝐨𝐫𝐤𝐥𝐨𝐚𝐝 𝐝𝐫𝐢𝐟𝐭 ↳ Runtime environments diverge faster than policies evolve → 𝐒𝐚𝐚𝐒 𝐬𝐮𝐩𝐩𝐥𝐲 𝐜𝐡𝐚𝐢𝐧 𝐫𝐢𝐬𝐤 ↳ Third-party integrations expand enterprise exposure silently → 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐭𝐞𝐥𝐞𝐦𝐞𝐭𝐫𝐲 𝐨𝐯𝐞𝐫𝐥𝐨𝐚𝐝 ↳ More alerts without business context reduces response quality The biggest mistake organisations still make: Treating cloud security as a prevention-only problem. But mature enterprises understand: Security architecture is really about controllability at scale. Because when visibility breaks: Governance breaks. Trust breaks. Operational resilience breaks. The organisations leading securely in 2026 are not the ones with the most dashboards. They are the ones reducing architectural uncertainty before it becomes enterprise risk. P.S. Which hidden cloud security gap do you think enterprises are underestimating most today: machine identity sprawl, shadow APIs, or AI infrastructure governance? Follow Dinesh Anbumani for more insights

🚨 𝟱 𝗡𝗘𝗪 𝗛𝗮𝗻𝗱𝘀-𝗼𝗻 𝗟𝗮𝗯𝘀 🚨 I just published five brand new hands-on labs within an all-new 𝗣𝗿𝗼𝗮𝗰𝘁𝗶𝘃𝗲 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗶𝗻 𝗬𝗼𝘂𝗿 𝗔𝗪𝗦 𝗖𝗜/𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 path for you to grow your security skill sets within AWS over at Pluralsight! The cool thing is each lab builds on the previous ending stages of the one before it, so it's like having 𝗳𝗶𝘃𝗲 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗮𝗹𝗹 𝗶𝗻 𝗼𝗻𝗲! The pain this path addresses is familiar to anyone who's shipped infrastructure as code: by the time a misconfigured S3 bucket or an over-permissive IAM role gets caught, it might already be deployed, only getting flagged in a post-deployment audit or a manual review that happened too late to be cheap to fix. This path's whole argument is that those checks belong 𝗶𝗻𝘀𝗶𝗱𝗲 𝘁𝗵𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲, running automatically on every change, behaving like fast unit tests that fail loudly before anything reaches an account! Here is a brief summary of each lab 👇🏼 🧪 𝗟𝗮𝗯 𝟭: 𝗜𝗻𝘀𝗲𝗿𝘁𝗶𝗻𝗴 𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗦𝘁𝗮𝗴𝗲 > Insert a placeholder governance stage between Source and Deploy within an AWS CodePipeline governance pipeline, wired to a CodeBuild project, and confirm it runs. 🧪 𝗟𝗮𝗯 𝟮: 𝗨𝘀𝗶𝗻𝗴 𝗦𝘁𝗮𝘁𝗶𝗰 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘁𝗼 𝗗𝗲𝘁𝗲𝗰𝘁 𝗖𝗹𝗼𝘂𝗱𝗙𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗠𝗶𝘀𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻𝘀 > Configure buildspec commands to run cfn-lint in the governance stage that was added in the first lab, catching issues and blocking non-compliant templates 🧪 𝗟𝗮𝗯 𝟯: 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗻𝗴 𝗜𝗔𝗠 𝗣𝗼𝗹𝗶𝗰𝗶𝗲𝘀 𝗮𝘀 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗨𝗻𝗶𝘁 𝗧𝗲𝘀𝘁𝘀 > Templates can declare overly permissive IAM policies that linting alone won't catch. So now you add a separate governance stage integrating cfn-guard to scan IAM and resource policies in CloudFormation templates. 🧪 𝗟𝗮𝗯 𝟰: 𝗥𝘂𝗻𝗻𝗶𝗻𝗴 𝗮 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝘁 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗖𝗵𝗲𝗰𝗸 𝗶𝗻 𝗮𝗻 𝗔𝗪𝗦 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 > You need to confirm the assembled controls let good changes through, not just block bad ones. Identify and fix the portion of a supplied CloudFormation template that's blocking deployment so it passes the full pipeline. 🧪 𝗟𝗮𝗯 𝟱: 𝗙𝗮𝗶𝗹𝗶𝗻𝗴 𝗮 𝗥𝗶𝘀𝗸𝘆 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗖𝗼𝗻𝘁𝗿𝗼𝗹𝘀 > A governance pipeline is only trustworthy if you can prove it blocks risk and diagnose why. This time you push a deliberately risky change, then root-cause the failure by reading CodeBuild logs to find which control fired and on which line. -- This path of labs is all about 𝘀𝗵𝗶𝗳𝘁𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗹𝗲𝗳𝘁 within your CI/CD pipelines within AWS. Be sure to check them out. Links to each will be in the comments! 👇🏼 P.S. Keep an eye out for a brand new challenge lab that builds off the concepts you learn throughout this series of labs coming VERY soon. 👀

𝗭𝗲𝗿𝗼 𝗧𝗿𝘂𝘀𝘁 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗼𝗻 𝗔𝗪𝗦: 𝗟𝗮𝘆𝗲𝗿𝗶𝗻𝗴 𝗬𝗼𝘂𝗿 𝗙𝗶𝗿𝘀𝘁 𝗟𝗶𝗻𝗲𝘀 𝗼𝗳 𝗗𝗲𝗳𝗲𝗻𝘀𝗲 Cyber threats are more intelligent than ever, and legacy security models that rely on perimeter defenses are obsolete. 𝗭𝗲𝗿𝗼 𝗧𝗿𝘂𝘀𝘁, 𝗮 "𝗻𝗲𝘃𝗲𝗿 𝘁𝗿𝘂𝘀𝘁, 𝗮𝗹𝘄𝗮𝘆𝘀 𝘃𝗲𝗿𝗶𝗳𝘆" 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵, 𝗶𝘀 𝗻𝗼𝘄 𝘁𝗵𝗲 𝗴𝗼𝗹𝗱 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱.  Here's how to implement it effectively on AWS, step by step: 1️⃣ 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆: 𝗬𝗼𝘂𝗿 𝗙𝗶𝗿𝘀𝘁 𝗟𝗶𝗻𝗲 𝗼𝗳 𝗗𝗲𝗳𝗲𝗻𝘀𝗲 In Zero Trust, identity replaces the traditional perimeter. Start here: • 𝗘𝗻𝗳𝗼𝗿𝗰𝗲 𝗟𝗲𝗮𝘀𝘁 𝗣𝗿𝗶𝘃𝗶𝗹𝗲𝗴𝗲: Restrict IAM roles/policies to only necessary permissions. • 𝗠𝗮𝗻𝗱𝗮𝘁𝗲 𝗠𝘂𝗹𝘁𝗶-𝗙𝗮𝗰𝘁𝗼𝗿 𝗔𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗶𝗼𝗻 (𝗠𝗙𝗔): Require MFA for all users, especially root/admin accounts. • 𝗔𝘂𝗱𝗶𝘁 𝗥𝗲𝗹𝗲𝗻𝘁𝗹𝗲𝘀𝘀𝗹𝘆: Use AWS CloudTrail to log every API call and detect unauthorized access. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: 81% of breaches involve stolen credentials. Locking down identity closes the most significant attack vector. 2️⃣ 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗠𝗶𝗰𝗿𝗼-𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: 𝗟𝗼𝗰𝗸 𝗗𝗼𝘄𝗻 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 Isolate workloads and minimize lateral movement: • 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗚𝗿𝗼𝘂𝗽𝘀 & 𝗡𝗔𝗖𝗟𝘀: Apply granular rules (e.g., "Only allow port 443 from this service"). • 𝗔𝗪𝗦 𝗣𝗿𝗶𝘃𝗮𝘁𝗲𝗟𝗶𝗻𝗸: Access services like S3 or DynamoDB without exposing data to the public internet. • 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗣𝗼𝗹𝗶𝗰𝗶𝗲𝘀 (𝗦𝗖𝗣𝘀): Prevent risky actions (e.g., disabling security controls) across your AWS Organization. 𝗣𝗿𝗼 𝗧𝗶𝗽: Pair segmentation with VPC Flow Logs to monitor traffic patterns and spot anomalies. 3️⃣ 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴: 𝗖𝗮𝘁𝗰𝗵 𝗧𝗵𝗿𝗲𝗮𝘁𝘀 𝗶𝗻 𝗥𝗲𝗮𝗹 𝗧𝗶𝗺𝗲 Visibility is non-negotiable: • 𝗔𝗪𝗦 𝗚𝘂𝗮𝗿𝗱𝗗𝘂𝘁𝘆: Machine learning detects compromised credentials, crypto-mining, and suspicious API activity. • 𝗔𝗪𝗦 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗛𝘂𝗯: Centralize findings from GuardDuty, Config, and third-party tools (e.g., CrowdStrike). • 𝗔𝗪𝗦 𝗖𝗼𝗻𝗳𝗶𝗴: Automatically assess resource compliance (e.g., "Is S3 encryption enabled?"). 𝗥𝗲𝗮𝗰𝘁 𝗙𝗮𝘀𝘁𝗲𝗿: Use Amazon EventBridge to trigger Lambda functions for auto-remediation (e.g., revoking access if GuardDuty flags an IP). ⬆️ 𝗣𝗮𝗿𝘁 𝟮 𝗱𝗿𝗼𝗽𝘀 𝘁𝗼𝗺𝗼𝗿𝗿𝗼𝘄: We'll dive into encryption, scaling with automation, and real-world Zero Trust workflows. 𝗬𝗼𝘂𝗿 𝘁𝘂𝗿𝗻: Have you enabled GuardDuty or MFA yet? #AWS #awscommunity #AWSSecurity #ZeroTrust #CloudSecurity #DevSecOps #TechLeadership

🚀 Unlocking AWS Security: A Comprehensive Guide to Cloud Pentesting 🔥As more businesses move their critical operations to the cloud, Amazon Web Services (AWS) is becoming a prime target for cyber attackers. Understanding the nuances of AWS Pentesting is now more crucial than ever for maintaining a robust security posture. The cheatsheet I’ve reviewed dives deep into the essential tools and techniques every cybersecurity professional should master. 🔍 Key Takeaways: Identity & Access Management (IAM): Gain insights on privilege escalation, how to identify shadow admins, and enumerate IAM permissions effectively. Metadata Service Attacks: Learn to exploit metadata SSRF vulnerabilities in EC2 and Fargate to steal sensitive IAM credentials. Backdoors and Persistence: Explore advanced backdoor methods using IAM policies, Lambda functions, and IAM roles to maintain long-term access. SSRF and Instance Hijacking: Understand how Server-Side Request Forgery (SSRF) can be leveraged to hijack instances or gain administrative privileges. S3 Buckets & Data Exfiltration: Tips on discovering publicly exposed S3 buckets, conducting data exfiltration, and leveraging vulnerabilities in S3 policies. 💡 Tools of the Trade: Pacu for AWS exploitation and SkyArk for discovering privileged accounts. ScoutSuite for cloud environment security audits. Cloudsplaining to identify and remediate IAM security risks. CloudMapper for visualizing AWS infrastructure. WeirdAAL for AWS privilege escalation and persistence attacks. 🌐 AWS security requires constant vigilance and staying up-to-date with the latest pentesting strategies. If you’re looking to strengthen your AWS defenses, this guide is a must-read! #AWS #CloudSecurity #CloudPentesting #CyberSecurity #EthicalHacking #SSRF #IAMSecurity #CloudCompliance #PentestTools #DataExfiltration #Infosec #CyberDefense #Pentesting #RedTeam #BlueTeam #AWSIAM #LambdaSecurity #EC2Exploitation #CloudThreats