Justine Coleman from The Hill is A Manipulative Media Hack

Justine Coleman is an media hack

On October 15, 2020 at 9:20 PM, Justin Coleman, a breaking news reporter with The Hill, published a ±640 word piece entitled

Intelligence officials warned Trump that Giuliani was target of Russian influence campaign

On the same day at 11:05 PM (105 minutes later), she rushed to publish a second ±880 word piece entitled:

Feds investigating if alleged Hunter Biden emails connected to foreign intelligence operation

In the first article, Coleman claimed that four former US intelligence officials that were ‘familiar with the matter’ said that the Hunter Biden emails and images published by the New Your Post are part of an influence operation by Russian intelligence. In the second article, she repeated the same claim and added that the materials are not being published by Twitter and Facebook because they violated their “hacked materials policy”.

Ignoring for a second the unfounded claim that these documents were obtained by Russian intelligence when they hacked Burisma. Coleman’s allegations about the inability to authenticate the emails and that the images are fabricated seem legitimate…that is, until you evaluate her credentials to make these statements, her articles, and her sources. Running Coleman through various analytics shows the following:

  1. She is a new hire at The Hill. According to her resume and bio, she has no commercial writing experience beyond a few fluffy internships.
  2. She lifted the articles from an NBC News piece by Ken Dilanian (the prince of impeachment) and a WaPo piece written by Ellen Nakashima (the queen of Russian collusion).
  3. She was instructed by her editor to publish the piece ‘as is’ with no independent verification of sources or their claims.
  4. The pieces were published by The Hill to help ‘amplify’ Dilanian’s NBC and Nakashima’s WaPo articles.
  5. All of Coleman’s, Dilanian’s, and Nakashima’s work is completely circular. None of these articles have even one substantiated piece of evidence.

 Justin Coleman LinkedIn Justin Coleman Resume
Image 1: The illustrious journalistic credentials of the highly trustworthy Justine Coleman

What about Justine Coleman’s expertise writing about national security and intelligence? Don’t bother looking for them, they are non existent. Her largest on-line footprint for original investigative work is her 8th grade science project. In this article, her ”Key to Awesomeness” is described as:

“Her science fair experiment was to determine how detergents, and the temperature of the water, affected stain removal.  “My experiment, basically, consisted of staining cotton pieces, washing them with different detergents and in different temperatures of water, and measuring the results,” said Justine.

To summarize it in a non-scientific language, she discovered that some of the stains came out, while others remained on the fabric, and that water temperature does, in fact, affect stain removal.

This basically concludes the listing of Justine Coleman’s professional qualifications to opine on any national security or intelligence issue or the authenticity of Hunter Biden’s images and emails.

Justine Coleman
Image 2
: Justine Coleman The national security and intelligence expert reporter who also discovered that water temperature and detergent type effects stain removal

Justine Coleman Student
Video 1
: October 2019, the George Washington University’s School of Media journalism student Justine Coleman expressing her disbelief that something that she wrote was worthy of publication by WaPo

Clearly, Coleman is somebody’s worn out sock puppet. It didn’t take much to figure out that Ellen Nakashima was the brain behind this little manipulative enterprise. So what’s the deal with Nakashima? If you are not familiar with this journalistic seraph, she is the reigning queen of the Russian DNC hack narrative. In May-June 2016, she actively colluded with Crowdstrike and the DNC’s senior leadership to develop the Russian source of the DNC hack claim. She then published that story on June 14, 2016. Then as now, she argued that the damaging DNC emails (the ones that describe how the DNC torpedoed Bernie Sanders) couldn’t be authenticated. On December 22, 2016, Nakashima again knowingly published and pimped another false article that promoted the Crowdstrike debunked claim that the Russians hacked the Ukrainian artillery using the same techniques they allegedly used on the DNC. 

What about the identify of the four anonymous former US intelligence officials that provided Nakashima with this information? It turns out that they are not anonymous at all. Just like the four blind mice, they are mere literary devices, they don’t exist! As with the DNC hack fiction, Nakashima completely made them up.

Bottom line is that the Hunter Biden images published by the New York Post have already been proven authentic. The same applies to his video, images, texts, emails, and other digital content that came from his laptop.

References and Sources
XRVision Sentinel AI Platform – Face recognition, image reconstruction, and object classification Hunter Biden Laptop Images Are Authentic – Forensic evaluation of two of Hunter Biden’s images
Who Done it?  – A deep dive into the alleged DNC email hack
The 4 Most Damaging Emails From the DNC WikiLeaks Dump

A Sampling from Ellen Nakashima’s Russian Collusion Repertoire
White House was warned Giuliani was target of Russian intelligence operation to feed misinformation to Trump – Oct 15, 2020

Microsoft seeks to disrupt Russian criminal botnet it fears could seek to sow confusion in the presidential election – Oct 12, 2020

Russia trying to stoke societal tensions and white supremacy is the most lethal threat to the United States, new DHS report says  – Oct 6, 2020

Mueller report highlights scope of election security challenge – April 20, 2019

Through email leaks and propaganda, Russians sought to elect Trump – April 18, 2019

Copyright 2020 Yaacov Apelbaum, All Rights Reserved.

Hunter Biden Laptop Images Are Authentic

Authentic

The following composite shows the results of a image authentication and evaluation tests performed on two images from the ‘Hunter Biden laptop’ collection. The Biden campaign and various MSM apologists claims that they are fakes. The results of the image analysis beg to differ:

  1. The two images match Hunter Biden on face recognition within a 98% certainty (using a validated image as the reference) 
  2. The object in Hunter Biden’s mouth matched a glass crack pipe within a 93% certainty 
  3. Both images came back as negative on a wide range of tampering and deepfake manipulations

Conclusion, these are authentic images within a probability >90%.

Hunter Biden Laptop Images
Image 1:
Authentication and validation of two images from the ‘Hunter Biden laptop’ collection

If you are not getting the relevance of Vadym Pozharskyi, the top Burisma adviser emailing Hunter asking for “advice on how you could use your influence”, the following composite may be of some help. Seen below is Vadym Pozharskyi in situ at an Atlantic Council event with former senior state department officials in the Obama administration including: Evelyn Farkas, Ambassador John Herbst, and Ambassador Roman Popadiuk. All hard at work unselfishly promoting the interests of Burisma. Why do you ask?  Because they are just nice like that.

AC John Herbst and Farkas

References and Sources
XRVision Sentinel AI Platform – Face recognition, image reconstruction, and object classification

Sampling of the Tests Performed on Imagery
Based AI based face recognition and deepfake detection. I’ve also performed a battery of forensic image analysis tests that included functions such as:

Double Quantization – These types of inconsistencies occur when a foreign object is inserted in a JPEG image. When the new image is saved, the untampered part of the image will have been compressed twice, while the inserted region only once. In this case, the tampered area should appear red while the rest of the image blue. If other colors are present (green, yellow) then no conclusion can be made.

Error Level Analysis –  These types of inconsistencies are produced by recompressing the image as a JPEG of quality 75 and subtracting the new image from the old. The resulting image of differences is then enhanced and displayed. Areas of interest are those with higher values than other similar parts of the image. Only similar regions should be compared, i.e. edges should be compared to edges, textures to textures, and uniform regions to uniform regions. Color discrepancies (commonly blue regions) are also generally suspicious.

Median Noise Residuals – These type of inconsistencies are based on isolating the almost-invisible image noise through median filtering. When interpreting the results, areas of interest are those that return higher (i.e. brighter) values than other similar parts of the image. Only similar regions are compared, i.e. edges are compared to edges, textures to textures, and uniform regions to uniform regions.

Compression anomalies 1 – JPEG compression operates in an 8-by-8 grid, which is near-invisible but detectable. Adding or moving an object on an image may locally disrupt this grid. The GRIDS algorithm seeks such discrepancies, and highlights them locally. The algorithm produces local red/orange “blobs” where it detects grid discrepancies. Generally, the GRIDS algorithm is less distracted by textures in the image, and focuses on grid disturbances.

Compression anomalies 2 – JPEG compression operates in an 8-by-8 grid, which is near-invisible but detectable. Adding or moving an object on an image may locally disrupt this grid. The GRIDS-Inverse algorithm is complementary to GRIDS in seeking such discrepancies. The algorithm produces local blue “blobs” where it detects grid discrepancies. Generally, the GRIDS algorithm is less distracted by textures in the image, and focuses on grid disturbances. However, it should mostly be interpreted in combination with other algorithm outputs that highlight the same regions.

Compression anomalies 3 – JPEG compression operates in an 8-by-8 grid, which is near-invisible but detectable. Adding or moving an object on an image may locally disrupt this grid. The BLOCK algorithm detects the image grid and looks for local discrepancies. Any coherent region with different color to its surroundings may correspond to tampering, although reds and yellows against a blue background are the most typical indication of tampering.

Compression anomalies 4 – The JPEG Ghosts algorithm is based on recompressing the image in multiple different qualities and subtracting each of them from the original. The resulting difference images are post-processed to highlight regions that stand out and are likely to originate from a different JPEG image. Then, the images most likely to contain interesting findings are selected (i.e. those that feature localized inconsistencies). Consistent yellow regions against a blue background may correspond to traces of tampering, especially if they do not correspond to edges, but to entire regions.

Noise anomalies – Each image carries invisible, high-frequency noise that is the result of the capturing process as well as the compression. The Discrete Wavelet Noise algorithm filters the image and calculates the local noise distribution at each part of the image. Regions that differ from the rest of the image are highlighted in strong red, and are likely to originate from other images.

Copyright 2020 Yaacov Apelbaum, All Rights Reserved.