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Airbnb Engineering & Data Science
airbnb.ioAirbnb.io Open SourceEventsBlogGithubCareersAirbnb.io BinaryAlertServerless real-time and retroactive malware detection705By Austin Byers, @mimeframe, Dai
.io > airbnb.io
SEO audit: Content analysis
Language | Error! No language localisation is found. | ||||||||||||||||||||||||||||||||||||
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Title | Airbnb Engineering & Data Science | ||||||||||||||||||||||||||||||||||||
Text / HTML ratio | 38 % | ||||||||||||||||||||||||||||||||||||
Frame | Excellent! The website does not use iFrame solutions. | ||||||||||||||||||||||||||||||||||||
Flash | Excellent! The website does not have any flash contents. | ||||||||||||||||||||||||||||||||||||
Keywords cloud | BinaryAlert YARA files bucket S3 file AWS CareersDesign immediately uploaded analysis Lambda entire rules SNS alerts retroactive Serverless Airbnb deploy | ||||||||||||||||||||||||||||||||||||
Keywords consistency |
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Headings |
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Images | We found 5 images on this web page. |
SEO Keywords (Single)
Keyword | Occurrence | Density |
---|---|---|
BinaryAlert | 9 | 0.45 % |
YARA | 7 | 0.35 % |
files | 5 | 0.25 % |
bucket | 5 | 0.25 % |
S3 | 5 | 0.25 % |
file | 4 | 0.20 % |
AWS | 4 | 0.20 % |
CareersDesign | 3 | 0.15 % |
immediately | 3 | 0.15 % |
uploaded | 3 | 0.15 % |
analysis | 3 | 0.15 % |
Lambda | 3 | 0.15 % |
entire | 3 | 0.15 % |
rules | 3 | 0.15 % |
SNS | 3 | 0.15 % |
alerts | 3 | 0.15 % |
retroactive | 3 | 0.15 % |
Serverless | 3 | 0.15 % |
Airbnb | 2 | 0.10 % |
deploy | 2 | 0.10 % |
SEO Keywords (Two Word)
Keyword | Occurrence | Density |
---|---|---|
S3 bucket | 5 | 0.25 % |
YARA rules | 3 | 0.15 % |
uploaded to | 3 | 0.15 % |
queued for | 2 | 0.10 % |
the entire | 2 | 0.10 % |
file uploaded | 2 | 0.10 % |
Lambda function | 2 | 0.10 % |
SNS topic | 2 | 0.10 % |
to deploy | 2 | 0.10 % |
deploy BinaryAlert | 2 | 0.10 % |
with a | 2 | 0.10 % |
to an | 2 | 0.10 % |
a single | 2 | 0.10 % |
for analysis | 2 | 0.10 % |
immediately queued | 2 | 0.10 % |
malware detection | 2 | 0.10 % |
retroactive malware | 2 | 0.10 % |
and retroactive | 2 | 0.10 % |
realtime and | 2 | 0.10 % |
Serverless realtime | 2 | 0.10 % |
SEO Keywords (Three Word)
Keyword | Occurrence | Density | Possible Spam |
---|---|---|---|
file uploaded to | 2 | 0.10 % | No |
immediately queued for | 2 | 0.10 % | No |
to deploy BinaryAlert | 2 | 0.10 % | No |
BinaryAlert S3 bucket | 2 | 0.10 % | No |
retroactive malware detection | 2 | 0.10 % | No |
and retroactive malware | 2 | 0.10 % | No |
realtime and retroactive | 2 | 0.10 % | No |
Serverless realtime and | 2 | 0.10 % | No |
bucket is immediately | 2 | 0.10 % | No |
S3 bucket is | 2 | 0.10 % | No |
© Airbnb Inc | 2 | 0.10 % | No |
queued for analysis | 2 | 0.10 % | No |
function runs every | 1 | 0.05 % | No |
runs every minute | 1 | 0.05 % | No |
Lambda function runs | 1 | 0.05 % | No |
every minute grouping | 1 | 0.05 % | No |
dispatching Lambda function | 1 | 0.05 % | No |
minute grouping files | 1 | 0.05 % | No |
Airbnbio Open Source | 1 | 0.05 % | No |
A dispatching Lambda | 1 | 0.05 % | No |
SEO Keywords (Four Word)
Keyword | Occurrence | Density | Possible Spam |
---|---|---|---|
S3 bucket is immediately | 2 | 0.10 % | No |
immediately queued for analysis | 2 | 0.10 % | No |
Serverless realtime and retroactive | 2 | 0.10 % | No |
realtime and retroactive malware | 2 | 0.10 % | No |
and retroactive malware detection | 2 | 0.10 % | No |
Airbnbio Open Source Events | 1 | 0.05 % | No |
function runs every minute | 1 | 0.05 % | No |
Lambda function runs every | 1 | 0.05 % | No |
dispatching Lambda function runs | 1 | 0.05 % | No |
A dispatching Lambda function | 1 | 0.05 % | No |
analysis A dispatching Lambda | 1 | 0.05 % | No |
for analysis A dispatching | 1 | 0.05 % | No |
queued for analysis A | 1 | 0.05 % | No |
is immediately queued for | 1 | 0.05 % | No |
the S3 bucket is | 1 | 0.05 % | No |
bucket is immediately queued | 1 | 0.05 % | No |
every minute grouping files | 1 | 0.05 % | No |
to the S3 bucket | 1 | 0.05 % | No |
uploaded to the S3 | 1 | 0.05 % | No |
file uploaded to the | 1 | 0.05 % | No |
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Airbnb Engineering & Data Science
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Airbnb Engineering & Data Science
Airbnb Engineering & Data Science
Airbnb Engineering & Data Science
Airbnb Engineering & Data Science
Airbnb Engineering & Data Science
Airbnb Engineering & Data Science
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Airbnb Engineering & Data Science
Airbnb.io Spined HTML
Airbnb Engineering & Data Science Airbnb.io Open SourceEventsBlogGithubCareersAirbnb.io BinaryAlertServerless real-time and retroactive malware detection705By Austin Byers, @mimeframe, Daimon GreavesServerless real-time and retroactive malware detection BinaryAlert is an open-source serverless AWS pipeline where any file uploaded to an S3 skillet is immediately scanned with a configurable set of YARA rules. An zestful will fire as soon as any match is found, giving an incident response team the worthiness to quickly contain the threat surpassing it spreads. Features Built with Amazon Web Services (AWS): An AWS worth is all you need to deploy BinaryAlert. Broad YARA Support: Add your own YARA rules and/or automatically clone them from third-party repos. Real-Time: Files uploaded to BinaryAlert (S3 bucket) are immediately queued for analysis. Serverless: All computation is handled by Lambda functions. No servers to manage ways stronger security and will-less scaling! Infrastructure-as-Code: The unshortened infrastructure is described with Terraform configuration files, enabling anyone to deploy BinaryAlert in a matter of minutes with a single command. Retroactive Analysis: After updating the YARA ruleset, BinaryAlert will retroactively scan the unshortened file corpus to find any new matches. Easily Configurable: BinaryAlert configuration is managed in a single Terraform variables file. Quality Code: Written in Python3 with unit tests and linting to ensure a wipe and reliable codebase. Low Cost: The AWS snout is based only on how many files are analyzed. Architecture The organization collects files and delivers them to their BinaryAlert S3 bucket. Files of interest could include executable binaries, email attachments, documents, etc. Every file uploaded to the S3 skillet is immediately queued for analysis. A dispatching Lambda function runs every minute, grouping files into batches and invoking up to dozens of analyzers in parallel. Each sharpshooter scans its files using a list of pre-compiled YARA rules. YARA matches are saved to DynamoDB and an zestful is sent to an SNS topic. We use StreamAlert to stimulation these alerts, but other organizations can instead slosh the alerts via email or any other supported SNS subscription. For retroactive analysis, a batching Lambda function enqueues the unshortened S3 skillet to be re-analyzed. Configurable CloudWatch alarms will trigger if any BinaryAlert component is behaving abnormally. This will notify a variegated SNS topic than the one used for YARA match alerts. LinksGithubDocumentationBlog PostSlack (unofficial)© Airbnb, Inc.© Airbnb, Inc.CareersDesignCareersDesignCareersDesign