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Solving API security through holistic
observability
APIDays NYC, July 28th 2021
Jean-Baptiste Aviat
Datadog AppSec engineer
CTO & Co-founder
Former (Red Team)
Email: jb@datadoghq.com
Twitter: @jbaviat
Podcast:
What is this? Worldwide life expectancy
multiplied by 2.4 in 150 years
Medicine in the past...
What happened in 150 years?
Microbiology
ECG
X-Ray
Radiotherapy
Blood transfer
Magnetic resonance imaging
CT scan
ECG
Correlate result from
various micro observations.
Wouldn’t have been
possible a century ago.
And now medicine students
have statistical classes.
Algorithm to evaluate a
macrocytic anemia
This progress came from medicine
ability to collect data, to exploit it, and to
make it usable by practitioners.
How do we translate this to security?
We have data from everywhere
Use data from everywhere (and not only left)
Observability
platform
Feedback Feedback
What do we actually need?
● Security resources are scarce
● They are spread thin
○ monitor production
○ help developers design secure systems
○ keep up with the business
● The systems are becoming more complex
→ security products have to make their life much easier and
help them focus on what matters
100%
Only requests
matching an attack
pattern
1%
Only attacks
matching an
existing route
.5%
Only attacks
targeting
what the
code does
.05%
Kill false positives.
Resurface threats.
By compounding security
events with contextual
information.
Only
attacks
on non
edge
services
.001%
100% API traffic
Query the framework
The attack is calling a real API endpoint
jb@datadoghq.com
6801-8226415-321-74
Find associated user
The attack is superficial: the API is on the edge
The attacked API actually performs a Cassandra query
The attack triggered a (caught) exception
request_params {
org_id 123 AND check = true UNION SELECT
email, pwd_hash, seed FROM users
}
NoSQL injection stealing user credentials
If user parameters are:
1. matching the database query
2. changing the query shape
That’s a proof of a NoSQL injection.
Let’s take this to the next level.
Instead of a dozen data points, hundreds
can be automatically gathered from your
production environment.
Information tight to a request
Information tight to an actor
Information tight to a service
True view about the
security context of an
API.
Combined with
statistical analysis,
provides the most
complete view in order
to monitor production
systems.
Holistic & code level API observability.
What’s beyond?
Remember: shift everywhere
we only focused on a subset of Operate + Monitor
Observability
platform
Feedback Feedback
Future:
● improve security data collection
● gather more context
● improve correlation
● make tools available to practitioners
Beyond the SIEM.
SIEM
Traces
Attacks OS
behavior
Errors
Vulns
Flattened information and disparate sources
(e.g. logs) prevents correlation
logs
logs
logs logs
logs
Cloud Security
Platform
Traces
Attacks OS
behavior
Errors
Correlation needs to happen on rich events
To allow efficient correlation
Vulns
Takeaways
Security evolves, but we need more data and more tools.
Don’t only shift left: shift everywhere.
Leverage observability from your engineering organization to
improve security monitoring:
● Production
● Software development lifecycle: tests, releases, designs
Correlate data using rich and coherent sources (rather than flat
and disparate)
Questions?

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apidays LIVE New York 2021 - Solving API security through holistic obervability by Jean-Baptiste Aviat, Datadog

  • 1. Solving API security through holistic observability APIDays NYC, July 28th 2021
  • 2. Jean-Baptiste Aviat Datadog AppSec engineer CTO & Co-founder Former (Red Team) Email: jb@datadoghq.com Twitter: @jbaviat Podcast:
  • 3. What is this? Worldwide life expectancy multiplied by 2.4 in 150 years
  • 4. Medicine in the past...
  • 5.
  • 6. What happened in 150 years? Microbiology ECG X-Ray Radiotherapy Blood transfer Magnetic resonance imaging CT scan ECG
  • 7. Correlate result from various micro observations. Wouldn’t have been possible a century ago. And now medicine students have statistical classes. Algorithm to evaluate a macrocytic anemia
  • 8. This progress came from medicine ability to collect data, to exploit it, and to make it usable by practitioners.
  • 9. How do we translate this to security?
  • 10. We have data from everywhere
  • 11. Use data from everywhere (and not only left) Observability platform Feedback Feedback
  • 12. What do we actually need? ● Security resources are scarce ● They are spread thin ○ monitor production ○ help developers design secure systems ○ keep up with the business ● The systems are becoming more complex → security products have to make their life much easier and help them focus on what matters
  • 13. 100% Only requests matching an attack pattern 1% Only attacks matching an existing route .5% Only attacks targeting what the code does .05% Kill false positives. Resurface threats. By compounding security events with contextual information. Only attacks on non edge services .001% 100% API traffic
  • 14. Query the framework The attack is calling a real API endpoint jb@datadoghq.com 6801-8226415-321-74 Find associated user
  • 15. The attack is superficial: the API is on the edge
  • 16. The attacked API actually performs a Cassandra query
  • 17. The attack triggered a (caught) exception
  • 18. request_params { org_id 123 AND check = true UNION SELECT email, pwd_hash, seed FROM users } NoSQL injection stealing user credentials If user parameters are: 1. matching the database query 2. changing the query shape That’s a proof of a NoSQL injection.
  • 19. Let’s take this to the next level. Instead of a dozen data points, hundreds can be automatically gathered from your production environment.
  • 20. Information tight to a request
  • 22. Information tight to a service
  • 23. True view about the security context of an API. Combined with statistical analysis, provides the most complete view in order to monitor production systems.
  • 24. Holistic & code level API observability. What’s beyond?
  • 25. Remember: shift everywhere we only focused on a subset of Operate + Monitor Observability platform Feedback Feedback
  • 26. Future: ● improve security data collection ● gather more context ● improve correlation ● make tools available to practitioners Beyond the SIEM.
  • 27. SIEM Traces Attacks OS behavior Errors Vulns Flattened information and disparate sources (e.g. logs) prevents correlation logs logs logs logs logs
  • 28. Cloud Security Platform Traces Attacks OS behavior Errors Correlation needs to happen on rich events To allow efficient correlation Vulns
  • 29. Takeaways Security evolves, but we need more data and more tools. Don’t only shift left: shift everywhere. Leverage observability from your engineering organization to improve security monitoring: ● Production ● Software development lifecycle: tests, releases, designs Correlate data using rich and coherent sources (rather than flat and disparate)