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Code Smell 263 - Squatting

Don't use guessable names in advance on mission-critical resources

TL;DR: Secure your cloud resources by avoiding predictable naming patterns.

Problems

Predictable names
Unauthorized access
Data exposure risks
Shadow resources
Account takeovers
Idor vulnerability
Premature Optimization

Solutions

Use unique bucket names with dark keys
Verify ownership on creation
Secure resources fully
Have indirections obfuscating real names
Book names to prevent squatting
Randomize names

Context
Resource squatting happens when attackers anticipate the naming patterns of cloud resources, like S3 buckets.
\
The attacker creates them in regions where the user hasn’t yet deployed resources.
\
User interaction with these attacker-owned resources can lead to severe security breaches like data exposure, unauthorized access, or account takeovers.
\
This vulnerability is critical in environments like AWS, where predictable naming conventions are often used.
\
Many systems avoid this indirection fearing the performance penalty which is a clear case of premature optimization.
Sample Code
Wrong
def create_bucket(account_id, region):
bucket_name = f"aws-glue-assets-{account_id}-{region}"
create_s3_bucket(bucket_name)
# This is deterministic and open

Right
import uuid

def create_bucket(account_id, region):
unique_id = uuid.uuid4().hex
# This number is not deterministic
# is a way to generate a random UUID (Universally Unique Identifier)
# in Python and then retrieve it as a hexadecimal string.
bucket_name = f"aws-glue-assets-{unique_id}-{account_id}-{region}"
create_s3_bucket(bucket_name)
verify_bucket_ownership(bucket_name, account_id)

Detection

[x] Automatic

A security audit can detect this smell by analyzing your resource names for predictability.
\
Look for patterns in names that an attacker can easily anticipate or guess.
\
Many automated tools and manual code reviews can help identify these risks.
Tags

Security

Level

[x] Intermediate

AI Generation
AI generators may create this smell using standard templates with predictable naming patterns.
\
Always customize and review generated code for security.
AI Detection
AI can help detect this smell if configured with rules that identify predictable or insecure resource naming conventions.
\
This is a security risk that requires an understanding of cloud infrastructure and potential attack vectors.
Conclusion
Avoiding predictable naming patterns is critical to securing your cloud resources.
\
Always use unique, obscure, hard-to-guess names, and also, verify resource ownership to protect against squatting attacks.
Relations
https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxiv?embedable=true
More Info
https://gbhackers.com/aws-vulnerability-remote-execution/?embedable=true
https://en.wikipedia.org/wiki/Cybersquatting?embedable=true
Disclaimer
Code Smells are my opinion.
Credits
Photo by Felix Koutchinski on Unsplash

The only system which is truly secure is one which is switched off and unplugged, locked in a titanium lined safe, buried in a concrete bunker, and is surrounded by nerve gas and very highly paid armed guards. Even then, I wouldn't stake my life on it.

Gene Spafford
https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true

This article is part of the CodeSmell Series.
How to Find the Stinky Parts of your Code

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