Found your neighbor on Parler map and want to see what video they posted, here's how.
Here is an easy to follow step by step guide on how to locate your neighbors who used Parler and then view and Download the videos they posted. A thread.
More from Software
As the year wrap's up, let's run through some of the worst public security mistakes and delays in fixes by AWS in 2020. A thread.
First, that time when an AWS employee posted confidential AWS customer information including including AWS access keys for those customer accounts to
Discovery by @SpenGietz that you can disable CloudTrail without triggering GuardDuty by using cloudtrail:PutEventSelectors to filter all events.
Amazon launched their bug bounty, but specifically excluded AWS, which has no bug bounty.
Repeated, over and over again examples of AWS having no change control over their Managed IAM policies, including the mistaken release of CheesepuffsServiceRolePolicy, AWSServiceRoleForThorInternalDevPolicy, AWSCodeArtifactReadOnlyAccess.json, AmazonCirrusGammaRoleForInstaller.
First, that time when an AWS employee posted confidential AWS customer information including including AWS access keys for those customer accounts to
Fresh data breach news-
— Chris Vickery (@VickerySec) January 23, 2020
Amazon AWS engineer exposes work-related keys, passwords, and documents marked "Amazon Confidential" via public Github repository: https://t.co/7gkIegnslx
Discovered within 30 minutes of exposure by my team at @UpGuard.
Discovery by @SpenGietz that you can disable CloudTrail without triggering GuardDuty by using cloudtrail:PutEventSelectors to filter all events.
"Disable" most #AWS #CloudTrail logging without triggering #GuardDuty:https://t.co/zVe4uSHog9
— Rhino Security Labs (@RhinoSecurity) April 23, 2020
Reported to AWS Security and it is not a bug.
Amazon launched their bug bounty, but specifically excluded AWS, which has no bug bounty.
Amazon Vulnerability Research Program - Doesn't include AWS D:https://t.co/stJHDG68pj#BugBounty #AWS
— Spencer Gietzen (@SpenGietz) April 22, 2020
Repeated, over and over again examples of AWS having no change control over their Managed IAM policies, including the mistaken release of CheesepuffsServiceRolePolicy, AWSServiceRoleForThorInternalDevPolicy, AWSCodeArtifactReadOnlyAccess.json, AmazonCirrusGammaRoleForInstaller.
@JuliaLMarcus @Iplaywithgerms This paper gives documentation on software (with causal reasoning, assumptions reviewed in appendix) for a parametric approach to estimating either "total effects" or "controlled direct effects" with competing events and time-varying
@Iplaywithgerms Total effects capture paths by which treatment affects competing event (e.g. protective total effect of lifesaving treatment on dementia may be wholly/partially due to effect on survival). Controlled direct effects do not capture these paths
@Iplaywithgerms More detailed reasoning on the difference and tradeoffs between total and controlled direct effects and causal reasoning in the point treatment context provided here along with description of some estimators and
@Iplaywithgerms If you are familiar with more robust approaches like IPW or even better TMLE for time-varying treatment, these are trivially adapted to go after the controlled direct effect by simply treating competing events like loss to follow-up (censoring). e.g.
@Iplaywithgerms Examples of IPW estimation of the total effect of a time-varying treatment described in Appendix D of this paper:
https://t.co/RNhcgTBMkb
And here
https://t.co/rMWmwFBWwV
Others in reference lists of above papers.
@Iplaywithgerms Total effects capture paths by which treatment affects competing event (e.g. protective total effect of lifesaving treatment on dementia may be wholly/partially due to effect on survival). Controlled direct effects do not capture these paths
@Iplaywithgerms More detailed reasoning on the difference and tradeoffs between total and controlled direct effects and causal reasoning in the point treatment context provided here along with description of some estimators and
@Iplaywithgerms If you are familiar with more robust approaches like IPW or even better TMLE for time-varying treatment, these are trivially adapted to go after the controlled direct effect by simply treating competing events like loss to follow-up (censoring). e.g.
@Iplaywithgerms Examples of IPW estimation of the total effect of a time-varying treatment described in Appendix D of this paper:
https://t.co/RNhcgTBMkb
And here
https://t.co/rMWmwFBWwV
Others in reference lists of above papers.